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MACMU,l,AN AND < <>,, I.iMHHt 

t.uNhuN ItfiMllA* . <'AJ,<Uir\ - M \tlKAs 



NKW VltUK ' HnvniN riIl('At,n 

t)Al.l.AS SAN MtANCtstit 

MA<:MIM,AN co. OK CANADA, i/n>, 




U MOW ut< KIM/', COM.hfrlC, 





TIIK Hubjtwl mutter of this book was first broached in the brain 
of Lfibuix, who, in thn dwHortation, written in his twenty-third 
yiwr, on the woilt* of ('hating thcs kings of Poland, conceived 
of Probability HM a braw.h of Logic, A few years before, "tin 
probK'iwC* in Urn words of Polsson, "propose *\ tin aust6re 
jaiiHi'ntHto jwr un honune du tmmdtt, a M rorigino du calcul 
des prohabilittV 1 In tlu. intervening centuries the algebraical 
oxoruiMttH, in whirli Uu* Chevalier do, la M(Sr6 interested Pascal, 
hav BH far {irrclcmiinatcul l\\ the leariuul world over the pro- 
fotui<!<*r tnt<|utri<iM <f UHI philoHophnr into thoso processes of 
bnmnti fiutulty which, by determining rcuisonablo preference, 
guidci our choice, that Probability if? oftanor reckoned with Mathe- 
watkm than with L(gic. There m much he^re, therefore, which is 
uovol, and, Insin^; novel, unsifted, inaccurate, or deficient. I 
profound iy HyHttnnatic conception of this subject for criticism 
tttul imlargwmwt at lh hatul of otlusrH, doubtful whether I 
myflolf am Hkttly tt> got much further, by waiting longer, 
with a work, which, beginning as a Fellowship "Dissertation, 
and interrupted bj^' tho war, has already extended over 
many yearn 

It may be perceived that I have been much influenced by 
W. & Johnson, 0. K Moore, and Itartrand liussell, that is 
to ay, by Cambridge, which, with great debts to the writers 
of Continental Europo, yet continues in direct succession 
the English tradition of Locke and Berkeley and Hume, of 
Mill and Sldgwick, who, in spite of their divergences of 


urn uniUul in a, prHt*r<nc*i' lor what is ninMcr of 
rm*.t, and have coiitM'ivrd l.hrir Hiihjtu'.t* SI.M si hriuu'.h rufJuT of 
Hcit^ico tliiLti of tin* c.rtiatiw itiia^ina-tiion, pr<si k writer,!, lnjiu^ 
tu h<, uiuhM'Hi.ood, 

,!. M, KKYNKS. 




M ft AN t Ml UK I'llUllAlllMTY , . . . .3 


arv IN lii-iiMTioN TO vine THICOHY OK KNOVVMGIHIK . 10 



THM PiUNc'ii'Mc OK iNnun^ttuwBroK , . .41 



or AHOUMT , . . - 71 












INTRODUCTORY . . . . . . .115 













BltilTIKS . . , . . . .158 








INTRODUCTION . . . . . . .217 

























POISSON, AND TCHEUYCHKPP 1 jf . . . . 337 



OP LAPLACE . . , . ' , .367 






DwTMitMTNATioN oj' 1 PjiODAiiiijiTY d posteriori THE METHODS 
OF LKXTH . . j/ . t .391 





INDEX ........ 459 




" J*ai dit plus d'une f ois qu'il faudrait une nouvelle esp&ce de logique, qui 
feraiteroit des degr6s de Probabilit6." LEIBNIZ. 

1 j PABT of .pur knowledge we ob^n .flj-pf.^.^ .^ji(Lpait by 
argument. The Theory of Probability is concerned with that 
part wnich we obtain by argument, and it treats of the different 
degrees in which the results so obtained are conclusive or in- 
conclusive. } 

In most branches of academic logic, such as the theory of the 
syllogism or the geometry of ideal space, all the arguments aim 
at demonstrative certainty. They claim to be conclusive. But 
many other arguments are rational and claim some weight with- 
out pretending to be certain, f In Metaphysics, in Science, and in 
Conduct, most of the arguments, upon which we habitually base- 
our rational beliefs, are admitted to be inconclusive in a greater 
or less degree. Thus for a philosophical treatment of these 
branches of knowledge, the study of probability is required. ] 

The course which the history of thought has led Logic to follow 
has encouraged the view that doubtful arguments are not within 
its scope. But in the actual exercise of reason we do not wait 
on certainty, or deem it irrational to depend on a doubtful 
argument. If logic investigates the general principles of valid 
thought, the study of arguments, to which it is rational to attach 
some weight, is as much a part of it as the study of those which 
*are demonstrative. ^ 

2. The terms cetrtww, and probable describe the various degrees 
of rational belief about a proposition which different amounts of 
knowledge authorise us to entertain. All propositions are truer 
or false, but the knowledge we have of them depends on our 
jkircumstances ; and while it is often convenient to speak oif 



propositions as certain or probable, this expresses strictly 
relationship in which they stand to a corpus of knowledge, actual or 
hypothetical, and not a characteristic of the propositions in them- 
selves. J A proposition is capable at the safae time of varying degrees 
of this relationship, depending upon the knowledge to which it ** 
related, so that it is without significance to call a proposition prob 
able unless we specify the knowledge to which we are relating it. 

To this extent, therefore, probability may be called sub- 
jective. But in the sense important to logic, probability is not 
subjective. It is not, that is to say, subject to human caprice. 
A proposition is not probable because we think it so. When once 
the facts are given which determine our knowledge, what is 
probable or improbable in these circumstances has been fixed 
objectively, and is independent of our opinion. The Theory of 
Probability is logical, therefore, because it is concerned with the 
degree of belief which it is rational to entertain in given conditions, 
and not merely with the actual beliefs of particular individuals, 
which may or may not be rational. 

Given the body of direct knowledge which constitutes our 
ultimate premisses, this theory tells us what further rational 
beliefs, certain or probable, can be derived by valid argument 
from our direct knowledge. This involves purely logical rela- 
tions between the propositions which embody our direct know- 
ledge and the propositions about which we? seek indixeet know- 
ledge. What particular propositions we select as the pcemiaises 
of owr argument naturally depends on subjective factors pectilfor 
to ourselves ; but the relations, in which other propo8i$Qas staad 
to these, tod which entitle us to probable beliefs, are objective 
and logical. ^ 

' 3. Let our premisses consist of any set of propositions ^ and 
our conclusion consist of any set of propositions a? $&$n, if & 
knowledge of h justifies a rational belief in a of degree %* we say 
jfchat there is a probability-relation of degree a between a ^cl &* 

In ordinary speech we often describe the oondusio^yfi bfcing 
doubtful, uncertain, or only probable. But, strictly ^^j&teJTOS 
ought to be applied, either to the degree of our rat4^^\^ief m 
the conclusion, or to the relation or argument betwwii %#o $et 
of propositions, knowledge of which would ofiord ^o$oii$ for a 
Corresponding degree of rational belief. 2 < '/-v '"'>"* * 

i This will be written afh a. * Se* also ChfrpW tt jjt^llf J 


r 4. With the term " event," which has baken hitherto so im- 
portant a place in the phraseology of the subject, I shall dis- 
pense altogether. 1 Writers on Probability have generally dealt 
with what they term the " happening " of " events." In the 
/problems which they first studied this did not involve much 
departure from common usage. But these expressions are now 
used in a way which is vague and unambiguous ; and it will be 
more than a verbal improvement to discuss the truth and, the 
probability of propositions instead of the occurrence and the 
probability of events. 2 

5. These general ideas are not likely to provoke much 
criticism. In the ordinary course of thought and argument^ 
we are constantly assuming that knowledge of one statement, 
while not proving the truth of a second, yields nevertheless^ 
some ground for believing it. We assert that we ought on the 
evidence to prefer such and such a belief. We claim rational 
grounds for assertions which are not conclusively demonstrated. 
We allow, in fact, that statements may be unproved, without, for 
that reason, being unfounded. And it does not seem on reflection 
that the information we convey by these expressions is wholly 
subjective. When we argue that Darwin gives valid grounds 
for our accepting his theory of natural selection, we do not simply 
mean that we are psychologically inclined to agree with him ; 
it is certain that we also intend to convey our belief that 
we are acting rationally in regarding his theory as prob- 
able. We believe that there is some real objective relation 
between Darwin's evidence and his conclusions, which is inde- 
pendent of the 'mere fact of our belief, and which is just as real 
and objective, though of a different degree, as that which would 
exist if the argument were as demonstrative as a syllogism. 
We are claiming, in fact, to cognise correctly a logical connection 
between one set of propositions which, we call our evidence and , 
which we suppose ourselves to know, and another set which we 
call oxu: conclusions, and to which we attach more or less weight 

1 Bxoept in those chapters (Chap. XVII., for example) where I am dealing 
chiefly with the work of others. 

* The first writer I know of to notice this was Anoillon ia Z>ottfe* sw lea 
&o* dfu colout des prtibobtf&te (1704) : "Dire qu'un fait passA present ou; $> 
venir eat probable, oW dire qu'une proposition est probable.' y The point wafc 
emphasised by Boole, Zmoe of Ttought, pp. 7 and 167. See also O 
vol. I p. 5, and Stumpf , Vber den Qegriff der 


according to the grounds supplied by the first. It is this type 
of objective relation between sets of propositions the type 
which, we claim to be correctly perceiving when we make such 
assertions as these to which the reader's attention must be 

6. It is not straining the use of words to speak of this as the 
-relation of probability. It is true that mathematicians have 
employed the term in a narrower sense ; for they have often 
confined it to the limited class of instances in which the relation 
is adapted to an algebraical treatment. But in common usage 
the word has never received this limitation. 

Students of probability in the sense which is meant by the 
authors of typical treatises on Wahrscheinlichkeitsrechnung or 
Cakul des probabititis, will find that I do eventually reach topics 
with which they are familiar. But in making a serious attempt 
to deal with the fundamental difficulties with which all students 
of mathematical probabilities have met and which are notoriously 
unsolved, we must begin at the beginning (or almost at the 
beginning) and treat our subject widely. As soon as mathe- 
matical probability ceases to be the merest algebra or pretends 
to guide our decisions, it immediately meets with problems 
against which its own weapons are quite powerless- And even 
if we wish later on to use probability in a narrow sense, it will 
be well to know first what it means in the widest. 

77. Between two sets of propositions, therefore, there exists 
a relation, in virtue of which, if we know the first, we can attach 
to the latter some degree of rational belief. This relation is the 
subject-matter of the logic of probability. 

A great deal of confusion and error has arisen out of a 
failure to take due account of this relational aspect of prob- 
ability. From the premisses " a implies 6 " and " a is true," we 
can conclude something about 6 namely that b is true which 
does not involve a. But, if a is so related to 6, that a knowledge 
of it renders a probable belief in 6 rational, we cannot conclude 
anything whatever about b which has not reference to a ; and it 
is not true that every set of self-consistent premisses which 
includes a has this same relation to b. It is as useless, there- 
fore, to say " b is probably " as it would be to say " 6 is equal," 
or " 6 is greater than," and as unwarranted to conclude ttat, 
because a makes b probable, therefore a and c together make b 


probable, as to argue that because a is less than 6, therefore a 
and c together are less than 6. 

Thus, when in ordinary speech we name some opinion as 
probable without further qualification, the phrase is generally 
elliptical. We mean that it is probable when certain considera- 
tions, implicitly or explicitly present to our minds at the moment, 
are taken into account. We use the word for the sake of short- 
ness, just as we speak of a place as being three miles distant, 
when we mean three miles distant from where we are then situated, 
or from some starting-point to which we tacitly refer. No 
proposition is in itself either probable or improbable, just as no 
place can be intrinsically distant ; and the probability of the 
same statement varies with the evidence presented, which is, 
as it were, its origin of reference. We may fix our attention 
on our own knowledge and, treating this as our origin, consider 
the probabilities of all other suppositions, according to the 
usual practice which leads to the elliptical form of common 
speech ; or we may, equally well, fix it on a proposed conclusion 
and consider what degree of probability this would derive from 
various sets of assumptions, which might constitute the corpus of 
knowledge of ourselves or others, or which are merely 

Reflection will show that this account harmonises with 
familiar experience. There is nothing novel in the supposition 
that the probability of a theory turns upon the evidence by which 
it is supported ; and it is common to assert that an opinion was 
probable on the evidence at first to hand, but on further informa- 
tion was untenable. As our knowledge or our hypothesis changes, 
our conclusions have new probabilities, not in themselves, but 
relatively to these new premisses. New logical relations have 
now become important, namely those between the conclusions 
which we are investigating and our new assumptions; but the 
old relations between the conclusions and the former assumptions 
still exist and are just as real as these new ones. It would be 
as absurd to deny that an opinion was probable, when at a later 
stage certain objections have come to light, as to deny, when 
we have reached our destination, that it was ever three^es 
distant ; and the opinion still is probable in relation to Jme old 
hypotheses, just as the destination is still three miles distant 
from our starting-pointX 


8. '\A definition of probability is not possible, unless it contents 
us to define degrees of the probability-relation by reference to 
degrees of rational belief. We cannot analyse tlie probability- 
relation in terms of simpler ideas. As soon as we have passed 
from the logic of implication and the categories of truth and 
falsehood to the logic of probability and the categories of know- 
ledge, ignorance, and rational belief, we are paying attention to 
a new logical relation in which, although it is logical, we were 
not previously interested, and which cannot be explained or 
defined in terms of our previous notions. 

This opinion is, from the nature of the case, incapable of posi- 
tive proof. The presumption in its favour must arise partly 
out of our failure to find a definition, and partly because the 
notion presents itself to the mind as something new and inde- 
pendent. If the statement that an opinion was probable on the 
evidence at first to hand, but became untenable on further in- 
formation, is not solely concerned with psychological belief, 1 
do not know how the element of logical doubt is to be defined, 
or how its substance is to be stated, in terms of the other 
indefinables of formal logic. The attempts at definition, which 
have been made hitherto, will be criticised in later chapters. 
I do not believe that any of them accurately represent that par- 
ticular logical relation which we have in our minds when we 
speak of the probability of an argument* 

In the great majority of cases the term " probable " seems to 
be used consistently by different persona to describe the same 
concept. Differences of opinion have not been due, I think, to 
a radical ambiguity of language. In any case a desire to reduce 
the indefinables of logic can 'easily be carried too far. Even if 
a definition is discoverable in the end, there is no harm in post- 
poning it until our enquiry into the object of definition is far 
advanced. In the case of " probability " the object befcw the 
mind is so familiar that the danger of misdescribing its qualities 
through lack of a definition is less than if it were a highly abstract 
entity far removed from the normal channels of thought, 

9. This chapter has served briefly to indicate, though not 
ix> x define, the subject matter of the book, Its object has 
been to emphasise the existence of a logical relation between two 
j&s of propositions in cases where it is not possible to argue 

demonstrativelv from one to the other. This is a contention 


of a most fundamental character. It is not entirely novel, but 
has seldom received due emphasis, is often overlooked, and 
sometimes denied. The view, that probability arises out of 
the existence of a specific relation between premiss and conclusion, 
depends for its acceptance upon a reflective judgment on the 
true character of the concept. It will be our object to discuss, 
under the title of- Probability, the principal properties of this 
relation. First, however, we must digress in order to consider 
briefly what we mean by knowledge, rational belief, and argument. 



1. I r>o not wish to become involved in questions of epistemology 
to which. I do not know the answer ; and I am anxious to reach 
as soon as possible the particular part of philosophy or logic 
which is the subject of this book. But some explanation is 
necessary if the reader is to be put in a position to understand 
the point of view from which the author sets out ; I will, there- 
fore, expand some part of what has been outlined or assumed 
in the first chapter. 

2. There is, first of all, the distinction between that part of 
oux belief which is rational and that part which is not. If a 
man believes something for a reason which is preposterous or 
for no reason at all, and what he believes turns out to be true for 
some reason not known to him., he cannot be said to believe it 
rationally, although he believes it and it is in fact true. On the 
other hand, a man may rationally believe a proposition to be 
probable, when it is in fact false. The distinction between 
rational belief and mere belief, therefore, is not the same as the 
, distinction between true beliefs and false beliefs. The highest 
degree of rational belief, which is termed certain rational belief, 
corresponds to knowledge. We may be said to know a thing 
when we have a certain rational belief in it, and vice versa. 3?or 
reasons which will appear from our account of probable degrees 
of rational belief in the following paragraph, it is preferable to 
regard knowledge as fundamental and to define rational betiqf by 
reference to it. 

/ 3. ^e come next to the distinction between that part of our 
rational belief which is certain and that p^t which is only 
probable. Belief, whether rational or not, is capable of degv$6; 
The highest degree of. rational belief, or rational certawp of 



belief, and its relation to knowledge have been introduced above. 
What, however, is the relation to knowledge of probable degrees 
of rational belief ? 

The proposition (say> q) that we know in this case is not the 
same as the proposition (say, p) in which we have a probable 
degree (say y a) of rational belief. If the evidence upon which 
we base our belief is A, then what we know, namely q, is that 
the proposition p bears the probability-relation of degree a to 
the set of propositions h ; and this knowledge of ours justifies 
us in a rational belief of degree a in the proposition p. It will 
be convenient to call propositions such as p, which do not contain 
assertions about probability-relations, " primary propositions " ; 
and propositions such as q, which assert the existence of a 
probability-relation, " secondary propositions." 1 ^ 

4. Thus knowledge of a proposition always corresponds to 
certainty of rational belief in it and at the same time to actual 
truth in the proposition itself. We cannot know a proposition 
unless it is in fact true. A probable degree of rational belief 
in a proposition, on the other hand, arises out of knowledge of 
some corresponding secondary proposition. A man may ration- 
ally believe a proposition to be probable when it is in fact false, 
if the secondary proposition on which he depends is true and 
certain; while a man cannot rationally believe a proposition 
to be probable even when it is in fact true, if the secondary 
proposition on which he depends is not true. Thus rational 
belief of whatever degree can only arise out of knowledge, 
although the knowledge may be of a proposition secondary, in 
the above sense, to the proposition in which the rational degree 
of belief is entertained. 

5. At this point it is desirable to colligate the three senses, 
in which the term probability has been so far employed. In its 
most fundamental sense, I think, it refers to the logical relation 
between two sets of propositions, which in 4 of Chapter L I 
have termed the probability-relation-. It is with this that I shall 
be mainly concerned in the greater part of this Treatise. Deriva- 
tive from thia sense, we have the sense in which, as above, the 
term probable is applied to the degrees of rational belief 

out of knowledge of secondary propositions which assert 

classification of " primary" and " secondary ". propositions 
sugg*rted to *ne by Mr, W. B. Johnson. . 


existence of probability-relations in the fundamental logical sense. 
Further it is often convenient, and not necessarily misleading, 
to apply the term probable to the proposition which is the object 
of the probable degree of rational belief, and which bears the 
probability-relation in question to the propositions comprising 
the evidence. 

6. I turn now to the distinction between direct and indirect 
knowledge between that part of our rational belief which we 
know directly and that part which we know by argument, 

We start from things, of variou' classes, with which we have, 
what I choose to call without reference to other uses of this term, 
direct acquaintance. Acquaintance with such things does not in 
itself constitute knowledge, although knowledge arises out of 
acquaintance with them. The most important classes of things 
with which we have direct acquaintance are our own sensations, 
which we may be said to experience., the ideas or meanings, about 
which we have thoughts and which we may be said to understand, 
and facts or characteristics or relations of sense-data or meanings, 
which we may be said to perceive ; experience, understanding, 
and perception being three forms of direct acquaintance. 

The objects of knowledge and belief as opposed to the 
objects of direct acquaintance which I term sensations, meanings, 
and perceptions I shall term propositions. 

Now our knowledge of propositions seems to be obtained in 
two ways : directly, as the result of contemplating the objects 
of acquaintance ; and indirectly, by argument, through perceiving 
the probability-relation of the proposition, about which we seek 
knowledge, to other propositions. In the second case, at any 
rate at first, what we know is not the proposition itself but, a 
secondary proposition involving it. "When we know a secondary 
proposition involving the proposition p as subject, we may be 
said to have indirect knowledge 0601$ p. 

Indirect knowledge about p may in suitable conditions lead 
to rational belief in p of an appropriate degree. If this degree 
ia that of certainty, then we have not merely indirect knowledge 
about p, but indirect knowledge of p. 

7. Let us take examples of direct knowledge. From ac- 
quaintance with a sensatioi^of yellow I can pass directly to a 
knowledge of the proposition " I have a sensation of yellow." 
Thorn, acquaintance with a sensation of yellow and with the 


meanings of " yellow," " colour/' " existence," I may be able 
to pass to a direct knowledge of the propositions cc I understand 
the meaning of yellow," " my sensation of yellow exists," " yellow 
is a colour." Thus, by some mental process of which it is 
difficult to give an account, we are able to pass from direct 
acquaintance with things to a knowledge of propositions about 
the things of which we have sensations or understand the 

Next, by the contemplation of propositions of which we have 
direct knowledge, we are able to pass indirectly to knowledge of or 
about other propositions. The mental process by which we pass 
from direct knowledge to indirect knowledge is in some cases and 
in some degree capable of analysis. We pass from a knowledge 
of the proposition a to a knowledge about the proposition 6 by per- 
ceiving a logical relation between them. With this logical rela- 
tion we have direct acquaintance. The logic of knowledge is 
mainly occupied with a study of the logical relations, direct 
acquaintance with which permits direct knowledge of the 
secondary proposition asserting the probability-relation, and so 
to indirect knowledge about, and in some cases of, the primary 

It is not always possible, however, to analyse the mental 
process in the case of indirect knowledge, or to say by the per- 
ception of what logical relation we have passed from the know- 
ledge of one proposition to knowledge about another. But 
although in some cases we seem to pass directly from one pro- 
position to another, I am inclined to believe that in all legitimate 
transitions of this kind some logical relation of the proper kind 
must exist between the propositions, even when we are not 
explicitly aware of it. In any case, '"whenever we pass to 
knowledge about one proposition by the contemplation of it in 
relation to another proposition of which we have knowledge 
e^ren when tke process is unanalysable I call it an argument. 
The knowledge, such as we have in ordinary thought by passing 
from one proposition to another without being able to say what 
logical relations, if any, we have perceived between them, may 
be termed uncompleted knowledge* And knowledge, which 
results from a distinct apprehension of the relevant logical 
relations, may be termed knowledge proper. 

8. In this way, therefore, I distinguish, between direct aaad 


indirect knowledge, between that part of our rational belief which 
is based on direct knowledge and that part which is based on 
argument. About what kinds of things we are capable of know- 
ing propositions directly, it is not easy to say. About our 
own existence, our own sense-data, some logical ideas, and some 
logical relations, it is usually agreed that we have direct know- 
ledge. Of the law of gravity, of the appearance of the other 
side of the moon, of the cure for phthisis, of the contents of 
Bradshaw, it is usually agreed that we do not have direct know- 
ledge. But many questions are in doubt. Of which logical 
ideas and relations we have direct acquaintance, as to whether 
we can ever know directly the existence of other people, and as 
to when we are knowing propositions about sense-data directly 
and when we are interpreting them it is not possible to give 
a clear answer. Moreover, there is another and peculiar kind 
of derivative knowledge by memory. 

At a given moment there is a great deal of our knowledge 
which we know neither directly nor by argument we remember 
it. We may remember it as knowledge, but forget how we origin- 
ally knew it. What we once knew and now consciously re- 
member, can fairly be called knowledge. But it is not easy to 
draw the line between conscious memory, unconscious memory 
or habit, and pure instinct or irrational associations of ideas 
(acquired or inherited) the last of which cannot fairly be called 
knowledge, for unlike the first two it did not even arise (in us at 
least) out of knowledge* Especially in such a case as that of 
what oux eyes tell us, it is difficult to distinguish between the 
different ways in which, our beliefe have arisen* We cannot 
always tell, therefore, what is remembered knowledge and what is 
not knowledge at all ; and when knowledge is remembered, we 
do not always remember at the same time whether, originally, it 
was direct or indirect. 

Although it is with knowledge by argument that I shall be 
mainly concerned in this book there is one Mud of direct know- 
ledge, namely of secondary propositions, with which I cannot 
help but be involved. In the case of every argument, it is only 
directly that we can know the secondary proposition which makes 
the argument itself valid and rational. When we know acme- 
thing by argument this must be through direct acquaintance 
with some logical relation between the conclusion and the premiss. 


In all knowledge, therefore, there is some direct element ; and 
logic can made purely mechanical. All it can do is 
so to arrange the reasoning that the logical relations, which 
have to be perceived directly, are made explicit and are of a 
simple kind. 

9. v It must be added that the term certainty is sometimes used 
in a merely psychological sense to describe a state of mind 
without reference to the logical grounds of the belief. With 
this sense I am not concerned. It is also used to describe the 
highest degree of rational belief ; and this is the sense relevant 
to our present purpose. The peculiarity of certainty is that 
knowledge of a secondary proposition involving certainty, 
together with knowledge of what stands in this secondary 
proposition in the position of evidence, leads to knowledge of, 
and not merely about, the corresponding primary proposition. 
Knowledge, on the other hand, of a secondary proposition in- 
volving a degree of probability lower than certainty, together 
with knowledge of the premiss of the secondary proposition, 
leads only to a rational belief of the appropriate degree in the 
primary proposition. The knowledge present in this latter case 
I have called knowledge about the primary proposition or con- 
clusion of the argument, as distinct from knowledge of it. 

Of probability we can say no more than that it is a lower degree 
of rational belief than certainty ; and we may say, if we like, 
that it deals with degrees of certainty. 1 Or we may make 
probability the more fundamental of the two and regard certainty 
as a special case of probability, as being, in fact, the maximum 
probability. Speaking somewhat loosely we may say that, if 
our premisses make the conclusion certain, then it follows from 
the premisses ; and if they make it very probable, then it very 
nearly follows from them.- 

It is sometimes useful to use the term " impossibility " as 
the negative correlative of " certainty," although the former 
sometimes has ft different set of associations. If a is certain, 
then the contradictory of a is impossible. If a knowledge of a 
makes b certain, then a knowledge of a makes the contradictory 

1 This view has often been taken, e.g., by Bernoulli and, incidentally, by 
Laplace ; also by Fries (see Czuber, JBntwicldung, p. 12). The view; occasion- 
ally held, that probability is concerned ytih. degrees of truth, arises out of a 
confusion between certainty and truth. Perhaps the Aristotelian doctrine 
that future events are neither true nor false arosaon this way, 

./ TTi 


of b impossible. Thus a proposition is impossible with respect 
to a given premiss, if it is disproved by the premiss ; and the 
relation of impossibility is the relation of minimum probability i 

10. We have distinguished between rational belief and irrational 
belief and also between rational beliefs which are certain in degree 
and those which are only probable. Knowledge lias been 
distinguished according as it is direct or indirect, according as it 
is of primary or secondary propositions, and according as it is 
of or merely about its object. 

In order that we may have a rational belief in a proposition p 
of the degree of certainty, it is necessary that one of two con- 
ditions should be fulfilled (i.) that we know p directly ; or (ii.) 
that we know a set of propositions h, and also know some secondary 
proposition q asserting a certainty-relation between p and A. 
In the latter case h may include secondary as well as primary 
propositions, but it is a necessary condition that all the pro- 
positions h should be known. In order that we may have rational 
belief in p of a lower degree of probability than certainty, it is 
necessary that we know a set of propositions h, and also know 
some secondary proposition q asserting a probability-relation 
between p and h. 

In the above account one possibility has been ruled out. It 
is assumed that we cannot have a rational belief in p of a degree 
less than certainty except through knowing a secondary pro- 
position of the prescribed type. Such belief can only arise, that 
is to say, by means of the perception of some probability-relation. 
To employ a common use of terms (though one inconsistent with 
the .use adopted above), I have assumed that all direct knowledge 
is certain. All knowledge, that is to say, which is obtained in a 
manner strictly direct by contemplation of the objects of acquaint- 
jpice and without any admixture whatever of argument and the 
Contemplation of the logical bearing of any other knowledge on 
this, corresponds to certam rational belief and not to a merely 
probable degree of rational belief. It is true that there do seem 
to be degrees of knowledge and rational belief, when the source of 

1 Necessity and Impossibility, in the senses in which these terms are used 
ia the theory of Modality, seem to correspond to the relations of Certainty and 
Impossibility in the theory of probability, the other modals, which comprise 
the intermediate degrees of possibility, corresponding to the intermediate 
degrees of probability. Almost up to the end of the seventeenth century 
the traditional treatment of modals is, in fact, a primitive attempt to bring 
the relations of probability within the scope of formal logic* 


the belief is solely in acquaintance, as there are when its source 
is in argument. But I think that this appearance arises partly 
out of the difficulty of distinguishing direct from indirect know- 
ledge, and partly out of a confusion between probable know- 
ledge and vague knowledge. I cannot attempt here to analyse 
the meaning of vague knowledge. It is certainly not the same 
thing as knowledge proper, whether certain or probable, and 
it does not seem likely that it is susceptible of strict logical 
treatment. At any rate I do not know how to deal with it, 
and in spite of its importance I will not complicate a difficult 
subject by endeavouring to treat adequately the theory of vague 

I assume then that only true propositions can be known, 
that the term " probable knowledge " ought to be replaced by 
the term " probable degree of rational belief," and that a probable 
degree of rational belief cannot arise directly but only as the 
result of an argument, out of the knowledge, that is to say, of 
a secondary proposition asserting some logical probability- 
relation in which the object of the belief stands to some known 
proposition. With arguments, if they exist, the ultimate pre- 
misses of which are known in some other manner than that 
described above, such as might be called " probable knowledge/* 
my theory is not adequate to deal without modification. 1 

For the objects of certain belief which is based on direct 
knowledge, as opposed to certain belief arising indirectly, there 
is a well -established expression.; propositions, in which our 
rational belief is both certain and direct, are said to be 

11. In conclusion, the relativity of knowledge to the individual 
may be briefly touched on. Some part of knowledge knowledge 
of our own existence or of our own sensations is clearly rela- 
tive to individual experience. We cannot speak of knowledge 
absolutely only of the knowledge of a particular person. Other 
parts of knowledge knowledge of the axioms of logic, for ex- 
ample may seem more objective. But we must admit, I think, 
that this too is relative to the constitution of the human mind, 
and that the constitution of the human mind may vary in some 
degree from man to man. What is self-evident to me and what 

1 I do not mean to imply, however, at any rate at present, that the ultimate 
premisses of an argument need always be primary propositions. 


PT. I 

I really know, may be only a probable belief to you, or may form 
no part of your rational beliefs at all. And this may be true 
not only of such, tilings as my existence, but of some logical axioms 
also. Some men indeed it is obviously the case may have a 
greater power of logical intuition than others. Further, the 
difference between some kinds of propositions over which human 
intuition seems to have power, and some over which it has none, 
may depend wholly upon the constitution of our minds and 
have no significance for a perfectly objective logic. We can no 
more assume that all true secondary propositions are or ought 
to be universally known than that all true primary propositions 
are known. The perceptions of some relations of probability 
may be outside the powers of some or all of us. 

What we know and what probability we can attribute to our 
rational beliefs is, therefore, subjective in the sense of being 
relative to the individual. But given the body of premisses which 
our subjective powers and circumstances supply to us, and given 
the kinds of logical relations, upon which arguments can be based 
and which we have the capacity to perceive, the conclusions, 
which it is rational for us to draw, stand to these premisses in an 
objective and wholly logical relation. Our logic is concerned 
with drawing conclusions by a series of steps of certain specified 
kinds from a limited body of premisses. 

With these brief indications as to the relation of Probability, 
as I understand it, to the Theory of Knowledge, I pass from 
problems of ultimate analysis and definition, which are not the 
primary subject matter of this book, to the logical theory and 
superstructure, which occupies an intermediate position between 
the ultimate problems and the applications of the theory, whether 
such applications take a generalised mathematical form or a 
concrete and particular one* For this purpose it would only 
encumber the exposition, without adding to its clearness or its 
accuracy, if I were to employ the perfectly exact terminology 
and minute refinements of language, which are necessary for the 
avoidance of error in very fundamental enquiries. While taking 
pains, therefore, to avoid any divergence between the substance 
of this chapter and of those which succeed it, and to employ only 
such periphrases as could be translated, if desired, into perfectly 
exact language, I shall not cut myself off from the convenient, 
but looser, expressions, which have been habitually employed 


by previous writers and Lave the advantage of being, in a general 
way at least, immediately intelligible to the reader. 1 

1 This question, which faces all contemporary writers on logical and philo- 
sophical subjects, is in my opinion much more a question of style and therefore 
to be settled on the same sort of considerations as other such questions than 
is generally supposed. There are occasions for very exact methods of state- 
ment, such as are employed in Mr. Russell's Principia Mathematica. But there 
are advantages also in writing the English of Hume. Mr. Moore has developed 
in Principia EtJiica an intermediate style which in his hands has force and 
beauty. But those writers, who strain after exaggerated precision without 
going the whole hog with Mr. Russell, are sometimes merely pedantic. They 
lose the reader's attention, and the repetitious complication of their phrases 
eludes his comprehension, without their really attaining, to compensate, 
a complete precision. Confusion of thought is not always best avoided by 
technical and unaccustomed expressions, to which the mind has no immediate 
reaction of understanding ; it is possible, under cover of a careful formalism, 
fco make statements, which, if expressed in plain language, the mind would 
immediately repudiate. There is much to be said, therefore, in favour of 
understanding the substance of what you are saying all the time, and of never 
reducing the substantives of your argument to the mental status of an x or y. 



1. I HAVE spoken of probability as being concerned with degrees 
of rational belief. This phrase implies that it is in some sense 
quantitative and perhaps capable of measurement. The theory 
of probable arguments must be much occupied, therefore, with 
comparisons of the respective weights which attach to different 
arguments. With this question we will now concern ourselves. 

It has been assumed hitherto as a matter of course that 
probability is, in the full and literal sense of the word, measurable. 
I shall hayc to limit, not extend, the popular doctrine. But, 
keeping my own theories in the background for the moment, 1 
will begin by discussing some existing opinions on the subject. 

2. It has been sometimes supposed that a numerical comparison 
between the degrees of any pair of probabilities is not only con- 
ceivable but is actually within our power. Bentham, for instance, 
in his Rationale of Judicial Evidence,* proposed a scale on which 
witnesses might mark the degree of their certainty ; and others 
have suggested seriously a ( barometer of probability.' 2 

That such comparison is theoretically possible, whether or not 
we are actually competent in every case to make the comparison, 
has been the generally accepted opinion. The following quota- 
tion 3 puts this point of view very well : 

" I do not see on what ground it can be doubted that every 

1 Book i ohap vi. (referred to by Venn). 

* The reader may be reminded of Gibbon's proposal that : " A Theological 
Barometer might be formed, of which the Cardinal (Baroniue) and our country- 
man, Dr. Middleton, should constitute the opposite and remote extremities, 
as the former sunk to the lowest degree of credulity, which was compatible with 
learning, and the latter rose to the highest pitch of scepticism, in any wise 
consistent with Religion." 

* W. 3T. Donkin, Phil Mag., 1861. He is replying to an article by J D. 
Forbes (PhiL Mag., Aug. 1849) which' had cast doubt upon this opinion. 



definite state of belief concerning a proposed hypothesis is in 
itself capable of being represented by a numerical expression, 
however difficult or impracticable it may be to ascertain its 
actual value. It would be very difficult to estimate in numbers 
the vis viva of all of the particles of a human body at any instant ; 
but no one doubts that it is capable of numerical expression. I 
mention this because I am not sure that Professor Forbes has 
distinguished the difficulty of ascertaining numbers in certain 
cases from a supposed difficulty of expression by means of numbers. 
The former difficulty is real, but merely relative to our knowledge 
and skill ; the latter, if real, would be absolute and inherent in 
the subject-matter., which I conceive is not the case." 

De Morgan held the same opinion on the ground that, wherever 
we have differences of degree, numerical comparison must be 
theoretically possible/ He assumes, that is to say, that all 
probabilities can be placed in an order of magnitude, and argues 
from this that they must be measurable. Philosophers, however, 
who are mathematicians, would no longer agree that, even if the 
premiss is sound, the conclusion follows from it. Object^ can 
be arranged in an order, which we can reasonably call one of 
degree or magnitude, without its being possible to conceive a 
system of measurement of the differences between the individuals. 

This opinion may also have been held by others, if not by 
De Morgan, in part because of the narrow associations which 
Probability has had for them. The Calculus of Probability has 
received far more attention than its logic, and mathematicians, 
under no compulsion to deal with the whole of the subject, have 
naturally confined their attention to those special cases, the exist- 
ence of which will be demonstrated at a later stage, where 
algebraical representation is possible. Probability has become 
associated, therefore, in the minds of theorists with those problems 
in which we are presented with a number of exclusive and ex- 
haustive alternatives of equal probability ; and the principles, which 
are readily applicable in such circumstances, have been supposed, 
without much further enquiry, to possess general validity. 

3. ; .It is also the case that theories of probability have been 

1 u Whenever the terms greater and less can be applied, there twice, thrice, 
etc., can be conceived, though not perhaps measured by us." " Theory of Prob- 
abilities," Encyclopaedia Metropolitan, p. 395. He is a little more guarded in 
his Formal Logic, pp. 174, 175 ; but arrives at the same conclusion so far as 
probability is concerned. ^ 


propounded and widely accepted, according to which its numerical 
character is necessarily involved in the definition. It is often 
said, for instance, that probability is the ratio of the number of 
" favourable cases " to the total number of (e cases." If this 
definition is accurate, it follows that every probability can be 
properly represented by a number and in fact is a number ; for 
a ratio is not a quantity at all. In the case also of definitions 
based upon statistical frequency, there must be by definition a 
numerical ratio corresponding to every probability. These 
definitions and the theories based on them will be discussed in 
Chapter VIII. ; they are connected with fundamental differences 
of opinion with which it is not necessary to burden the present 

4. If we pass from the opinions of theorists to the experience 
of practical men, it might perhaps be held that a presumption 
in favour of the numerical valuation of all probabilities can be 
based on the practice of underwriters and the willingness of 
Lloyd's to insure against practically any risk. Underwriters are 
actually willing, it might be urged, to name a numerical measure 
in every case, and to back their opinion with money. But this 
practice shows no more than that many probabilities are greater 
or less than some numerical measure, not that they themselves 
are numerically definite. It is sufficient for the underwriter if 
the premium he names exceeds the probable risk. But, apart 
from this, I doubt whether in extreme cases the process of thought, 
through which he goes before naming a premium, is wholly 
rational and determinate ; or that two equally intelligent brokers 
acting on the same evidence would always arrive at the same 
result. In the case, for instance, of insurances effected before 
a Budget, the figures quoted must be partly arbitrary. There is 
in them an element of caprice, and the broker's state of mind, 
when he quotes a figure, is like a bookmaker's when he names 
odds. Whilst he may be able to make sure of a profit, on the 
principles of the bookmaker, yet the individual figures that make 
up the book are, within certain limits, arbitrary. He may bo 
almost certain, that is to say, that there will not be new taxes on 
more than one of the articles tea, sugar, and whisky ; there 
may be an opinion abroad, reasonable or tmreasonable, that the 
likelihood is in the order whisky, tea, sugar ; and he may, 
therefore, be able to effect insurances for equal amounts in 


at 30 per cent, 40 per cent, and 45 per cent. He has thus made 
sure of a profit of 15 per cent, however absurd and arbitrary his 
quotations may be. It is not necessary for the success of under- 
writing on these lines that the probabilities of these new taxes 
are really measurable by the figures -^^and 1%%; it is sufficient 
that there should be merchants willing to insure at these rates. 
These merchants, moreover, may be wise to insure even if the 
quotations are partly arbitrary ; for they may run the risk of in- 
solvency unless their possible loss is thus limited. That the 
transaction is in principle one of bookmaking is shown by the 
fact that, if there is a specially large demand for insurance against 
one of the possibilities, the rate rises ; the probability has not 
changed, but the " book " is in danger of being upset. A Presi- 
dential election in the United States supplies a more precise 
example. On August 23, 1912, 60 per cent was quoted at Lloyd's 
to pay a total loss should Dr. Woodrow Wilson be elected, 30 per 
cent should Mr. Taft be elected, and 20 per cent should Mr. 
Roosevelt be elected. A broker, who could effect insurances 
in equal amounts against the election of each candidate, would be 
certain at these rates of- a profit of 10 per cent. Subsequent 
modifications of these terms would largely depend upon the 
number of applicants for each kind of policy. Is it possible to 
maintain that these figures in any way represent reasoned 
numerical estimates of probability ? 

In some insurances the arbitrary element seems even greater. 
Consider, for instance, the reinsurance rates for the Waratah, 
a vessel which disappeared in South African waters. The 
lapse of time made rates rise ; the departure of ships in search of 
her made them fall ; some nameless wreckage is found and they 
rise ; it is remembered that in similar circumstances thirty 
years ago a vessel floated, helpless but not seriously damaged, 
for two months, and they fall. Can it be pretended that the 
figures which were quoted from day to day 75 per cent, 83 per 
cent, 78 per cent were rationally determinate, or that the 
actual figure was not within wide limits arbitrary and due to 
the caprice of individuals ? In fact underwriters themselves 
distinguish between risks which are properly insurable, either 
because their probability can be estimated between comparatively 
narrow numerical limits or because it is possible to make a " book " 
wtich covers all possibilities, and other risks which cannot be 


dealt with in this way and which cannot form the basis of a regular 
business of insurance, although an occasional gamble may be 
indulged in. I believe, therefore, that the practice of under- 
writers weakens rather than supports the contention that all 
probabilities can be measured and estimated numerically. 

5. Another set of practical men, the lawyers, have been more 
subtle in this matter than the philosophers. 1 A distinction, 
interesting for our present purpose, between probabilities, which 
can be estimated within somewhat narrow limits, and those which 
cannot, has arisen in a series of judicial decisions respecting 
damages. The following extract 2 from the Times Law Reports 
seems to me to deal very clearly in a mixture of popular and legal 
phraseology, with the logical point at issue : 

This was an action brought by a breeder of racehorses to 
recover damages for breach of a contract. The contract was 
that Oyllene, a racehorse owned by the defendant, should in the 
season of the year 1909 serve one of the plaintiffs brood 
mares. In the summer of 1908 the defendant, without the con- 
sent of the plaintiff, sold Cyllene for 30,000 to go to South 
America. The plaintiff claimed a sum equal to the average 
profit he had made through having a mare served by Cyllene 
during the past four years. During those four years he had 
had four colts which had sold at 3300. Upon that basis his 
loss came to 700 guineas. 

Mr. Justice Jelf said that he was desirous, if he properly 
could, to find some mode of legally making the defendant com- 
pensate the plaintiff ; but the question of damages presented 
formidable and, to his mind, insuperable difficulties* The 
damages, if any, recoverable here must be either the estimated 
loss of profit or else nominal damages. The estimate could only 
be based on a succession of contingencies. Thus it was assumed 
that (inter alia) Cyllene would be alive and well at the time of the 
aded service ; that the mare sent would be well bred and not 
that she would not slip her foal ; and that the foal would 
be born alive and healthy. In a case of this kind he could only 

1 Leibniz notes the subtle distinctions made by Jurisconsults between 
degrees of probability ; and in the preface to a work, projected but unfinished, 
which was to have been entitled Ad stateram juris de gradibus probationum et 
probabilitatum he recommends them as models of logic in contingent questions 
(Couturat, Logi^ue de Ltibnjk, p. 240). 

2 I hare considerably expressed the original report (Sapwell v, Bass). 


rely on the weighing of chances ; and the law generally regarded 
damages which depended on the weighing of chances as too 
remote, and therefore irrecoverable. It was drawing the line 
between an estimate of damage based on probabilities, as in 
" Simpson v. L. and N.W.- Kailway Co." (1, Q.B.D., 274), where 
Cockburn, C.J., said : " To some extent, no doubt, the damage 
must be a matter of speculation, but that is no reason for not 
awarding any damages at all," and a claim for damages of a 
totally problematical character. He (Mr. Justice Jelf) thought 
the present case was well over the line. Having referred to 
" Mayne on Damages " (8th ed., p. 70), he pointed out that 
in "Watson v. Ambergah Eailway Co." (15, Jur., 448) Patteson, J., 
seemed to think that the chance of a prize might be taken into 
account in estimating the damages for breach of a contract to 
send a machine for loading barges by railway too late for a show ; 
but Erie, J., appeared to think such damage was too remote. 
In his Lordship's view the chance of winning a prize was not of 
sufficiently ascertainable value at the time the contract was made 
to be within the contemplation of the parties. Further, in the 
present case, the contingencies were far more numerous and 
uncertain. He would enter judgment for the plaintiff for nominal 
damages, which were all he was entitled to. They would be 
assessed at Is. 

One other similar case may be quoted in further elucidation 
of the same point, and because it also illustrates another point 
the importance of making clear the assumptions relative to which 
the probability is calculated. This case * arose out of an offer of 
a Beauty Prize 2 by the Daily Express. Out of 6000 photographs 
submitted, a number were to be selected and published in the 
newspaper in the following manner : 

The United Kingdom was to be divided into districts and the 
photographs of the selected candidates living in each district were 
to be submitted to the readers of the paper in the district, who 
were to select by their votes those whom they considered the 
most beautiful, and a MX, Seymour Hicks was then to make an 
appointment with the 50 ladies obtaining the greatest number 
of votes and himself select 12 of them* The plaintiff, who came 

i Chaplin v. Hicks (1911). 

* The prize was to be a theatrical engagemen^and, according to the article, 
the probability of subsequent marriage into the peerage. 


out head of one of the districts, submitted that she had not been 
given a reasonable opportunity of keeping an appointment, that 
she had thereby lost the value of her chance of one of the 12 
prizes, and claimed damages accordingly. The jury found that 
the defendant had not taken reasonable means to give the 
plaintiff an opportunity of presenting herself for selection, and 
assessed the damages, provided they were capable of assessment, 
at 100, the question of the possibility of assessment being post- 
poned. This was argued before Mr. Justice Pickford, and sub- 
sequently in the Court of Appeal before Lord Justices Vaughan 
Williams, Fletcher Moulton, and Farvvell. Two questions arose 
relative to what evidence ought the probability to be cal- 
culated, and was it numerically measurable ? Counsel for the 
defendant contended that, " if the value of the plaintiff's chance 
was to be considered, it must be the value as it stood at the begin- 
ning of the competition, not as it stood after she had been selected 
as one of the 50. As 6000 photographs had been sent in, and there 
was also the personal taste of the defendant as final arbiter to 
be considered, the value of the chance of success was really in- 
calculable." The first contention that she ought to be considered 
as one of 6000 not as one of 50 was plainly preposterous and did 
not hoodwink the court. But the other point, the personal 
taste of the arbiter, presented more difficulty. In estimating 
the chance, ought the Court to receive and take account of 
evidence respecting the arbiter's preferences in types of beauty ? 
Mr. Justice Pickford, without illuminating the question, held that 
the damages were capable of estimation. Lord Justice Vaughan 
Williams in giving judgment in the Court of Appeal argued as 
follows : 

As he understood it, there were some 50 competitors, and 
there were 12 prizes of equal value, so that the average chance 
of success was about one in four. It was then said that the 
questions which might arise in the minds of the persons who had 
to give the decisions were so numerous that it was impossible to 
apply the doctrine of averages. He did not agree. Then it 
was said that if precision and certainty were impossible in any 
oase it would be right to describe the damages a$ unassessable. 
He agreed that there might be damages so unassessable that the 
doctrine of averages was not possible of application because the 
figures necessary to be applied were not forthcoming. Several 


cases were fco be found in the reports where it had been so held, 
but he denied the proposition that because precision and certainty 
had not been arrived at, the jury had no function or duty to 
determine the damages. ... He (the Lord Justice) denied that 
the mere fact that you could not assess with precision and cer- 
tainty relieved a wrongdoer from paying damages for his breach of 
duty. He would not lay down that in every case it could be left 
to the jury to assess the damages ; there were cases where the 
loss was so dependent on the mere unrestricted volition of another 
person that it was impossible to arrive at any assessable loss 
from the breach. It was true that there was no market here ; 
the right to compete was personal and could not be transferred. 
He could not admit that a competitor who found herself one of 
50 could have gone into the market and sold her right to compete. 
At the same time the jurjr might reasonably have asked them- 
selves the question whether, if there was a right to compete, it 
could have been transferred, and at what price. Under these 
circumstances he thought the matter was one for the jury. 

The attitude of the Lord Justice is clear. The plaintiff had 
evidently suffered damage, and justice required that she should 
be compensated. But it was equally evident, that, relative to 
the completest information available and account being taken of 
the arbiter's personal taste, the probability could be by no means 
estimated with numerical precision. Further, it was impossible 
to say how much weight ought to be attached to the fact that 
the plaintiff had been head of her district (there were fewer than 
50 districts) ; yet it was plain that it made her chance better than 
the chances of those of the 50 left in, who were not head of their 
districts. Let rough justice be done, therefore. Let the case 
be simplified by ignoring some part of the evidence. The 
" doctrine of averages " is then applicable, or, in other words, 
the plaintiffs loss may be assessed at twelve-fiftieths of the 
value of the prise. 1 

6. How does the matter stand, then ? Whether or not such 
a thing is theoretically conceivable, no exercise of the practical 
judgment is possible, by which a numerical value can actually 
be given to the probability of every argument. So far from 

1 The jury in assessing the damages at 100, however, cannot have argued 
so subtly aa this ; for the average value of a prize (I have omitted the details 
beating on their value) could uotliave been fairly estimated so high as 400. 


our being able to measure them, it is not even clear that we are 
always able to place them in an order of magnitude. Nor has 
any theoretical rule for their evaluation ever been suggested. 

The doubt, in view of these facts, whether any two prob- 
abilities are in every case even theoretically capable of comparison 
in terms of numbers, has not, however, received serious considera- 
tion. There seems to me to be exceedingly strong reasons for 
entertaining the doubt. Let us examine a few more instances. 

7. Consider an induction or a generalisation. Ifc is usually 
held that each additional instance increases the generalisation's 
probability. A conclusion, which is based on three experiments 
in which the unessential conditions are varied, is more trust- 
worthy than if it were based on two. But what reason or 
principle can be adduced for attributing a numerical measure to 
the increase ? l 

Or, to take another class of instances, we may sometimes 
have some reason for supposing that one object belongs to a 
certain category if it has points of similarity to other known 
members of the category (e.g. if we are considering whether 
a certain picture should be ascribed to a certain painter), and 
the greater the similarity the greater the probability of our 
conclusion. But we cannot in these cases measure the increase ; 
we can say that the presence of certain peculiar marks in a 
picture increases the probability that the artist of whom those 
marks are known to be characteristic painted it, but we cannot 
say that the presence of these marks makes it two or three or 
any other number of times more probable than it would have 
been without them. We can say that one thing is more like a 
second object than it is like a third ; but there will very seldom be 
any meaning in saying that it is twice as like. Probability is, so 
far as measurement is concerned, closely analogous to similarity. 2 

1 It is true that Laplace and others (even amongst contemporary writers) 
have believed that the probability of an induction is measurable by mcanfl of a 
formula known as the rule of succession, according to which the probability of an 

induction based on n instances is n . Those who havo boon convinced by 

n -H * 

the reasoning employed to establish this rule must bo asked to postpone judg- 
ment until it has been examined in Chapter XXX. But wo may point out hero 
the absurdity of supposing that the odds are 2 to I in favour of a generalisation 
based on a single instance a conclusion which this formula would seem to 

2 There are very few writers on probability who havo explicitly admitted 
that probabilities, though in some sense quantitative, may bo incapable of 


Or consider the ordinary circumstances of life. We are out 
for a walk what is the probability that we shall reach home 
alive ? Has this always a numerical measure ? If a thunder- 
storm bursts upon us, the probability is less than it was before ; 
but is it changed by some definite numerical amount ? There 
might, of course, be data which would make these probabilities 
numerically comparable ; it might be argued that a knowledge 
of the statistics of death by lightning would make such a com- 
parison possible. But if such information is not included within 
the knowledge to which the probability is referred, this fact is 
not relevant to the probability actually in question and cannot 
affect its value. In some cases, moreover, where general statistics 
are available, the numerical probability which might be derived 
from them is inapplicable because of the presence of additional 
knowledge with regard to the particular case. Gibbon cal- 
culated his prospects of life from the volumes of vital statistics 
and the calculations of actuaries. But if a doctor had been called 
to his assistance the nice precision of these calculations would 
have become useless ; Gibbon's prospects would have been better 
or worse than before, but he would no longer have been able to 
calculate to within a day or week the period for which he then 
possessed an even chance of survival. 

In these instances we can, perhaps, arrange the probabilities 
in an order of magnitude and assert that the new datum 
strengthens or weakens the argument, although there is no 
basis for an estimate how much stronger or weaker the new 
argument is than the old. But in another class of instances is 
it even possible to arrange the probabilities in an order of magni- 
tude, or to say that one is the greater and the other less ? 

8, Consider three sets of experiments, each directed towards 
establishing a generalisation. The first set is more numerous ; 

numerical comparison. Edgeworth, " Philosophy of Chance " (Mind, 1884, p. 
225), admitted that " there may well be important quantitative, although not 
numerical, estimates ** of probabilities. Goldschmidt ( Wahrscheirilichkeitwech- 
nung, p. 43) may also bo cited as holding a somewhat similar opinion. He 
maintains that a lack of comparability in the grounds often stands in the way 
of the moasurability of the probable in ordinary usage, and that there are not 
necessarily good reasons for measuring the value of one argument against 
that of another. On the other hand, a numerical statement for the degree of the 
probable, although generally impossible, is not in itself contradictory to the 
notion ; and of three statements, relating to the same circumstances, we can 
well say that one is more probable than another, and that one is the most 
probable of the throe. 


in the second set the irrelevant conditions have been more 
carefully varied ; in the third case the generalisation in view 
is wider in scope than in the others. Which of these generalisa- 
tions is on such evidence the most probable ? There is, surely, 
no answer ; there is neither equality nor inequality between 
them. We cannot always weigh the analogy against the induc- 
tion, or the scope of the generalisation against the bulk of the 
evidence in support of it. If we have more grounds than 
before, comparison is possible ; but, if the grounds in the two 
cases are quite different, even a comparison of more and less, 
let alone numerical measurement, may be impossible. 

This leads up to a contention, which I have heard supported, 
that, although not all measurements and not all comparisons of 
probability are within our power, yet we can say in the case of 
every argument whether it is more or less likely than not. Is our 
expectation of rain, when we start out for a walk, always more 
likely than not, or less likely than not, or as likely as not ? I am 
prepared to argue that on some occasions none of these alternatives 
hold, and that it will be an arbitrary matter to decide for or 
against the umbrella. If the barometer is high, but the clouds are 
black, it is not always rational that one should prevail over the 
other in our minds, or even that we should balance them, 
though it will be rational to allow caprice to determine us and 
to waste no time on the debate. 

9, Some cases, therefore, there certainly are in which no 
rational basis has been discovered for numerical comparison. It 
is not the case here that the method of calculation, prescribed 
by theory, is beyond our powers or too laborious for actual 
application. No method of calculation, however impracticable, 
has been suggested. Nor have we any prima facie indications of 
the existence of a common unit to which the magnitudes of all 
probabilities are naturally referable. A degree of probability 
is not composed of some homogeneous material, and is not 
apparently divisible into parts of like character with one 
another. An assertion, that the magnitude of a given prob- 
ability is in a numerical ratio to the magnitude of every 
other, seems, therefore, unless it is based on one of the current 
definitions of probability, with which I shall deal separately 
in later chapters, to be altogether devoid of the kind of support, 
which can usually be supplied in the case of quantities of which 


the mensurability is not open to denial. It will be worth 
while, however, to pursue the argument a little further. 

10. There appear to be four alternatives. Either in some 
cases there is no probability at all ; or probabilities do not all 
belong to a single set of magnitudes measurable in terms of a 
common unit ; or these measures always exist, but in many 
cases are, and must remain, unknown ; or probabilities do 
belong to such a set and their measures are capable of being 
determined by us, although we are not always able so to 
determine them in practice. 

11. Laplace and his followers excluded the first two alter- 
natives. They argued that every conclusion has its place in 
the numerical range of probabilities from to 1, if only we "knew 
it, and they developed their theory of unknown probabilities. 

In dealing with this contention, we must be clear as to what 
we mean by saying that a probability is unknown. Do we mean 
unknown through lack of skill in arguing from given evidence, 
or unknown through lack of evidence ? The first is alone 
admissible, for new evidence would give us a new probability, 
not a fuller knowledge of the old one ; we have not discovered 
the probability of a statement on given evidence, by determining 
its probability in relation to quite different evidence. We must 
not allow the theory of unknown probabilities to gain plausibility 
from the second sense. A relation of probability does not yield 
us s as u, rule, information of much value, unless it invests the 
conclusion with a probability which lies between narrow numerical 
limits.' In ordinary practice, therefore, we do not always regard 
ourselves as knowing the probability of a conclusion, unless we 
can estimate it numerically. We are apt, that is to say, to 
restrict the use of the expression probable to these numerical 
examples, and to allege in other cases that the probability is 
unknown. We ttiight say, for example, that we do not know, 
when we go on a railway journey, the probability of death in a 
railway accident, unless we are told the statistics of accidents 
in former years ; or that we do not know our chances in a lottery, 
unless we are told the number of the tickets. But it must be 
clear upon reflection that if we use the term in this sense, which 
is no doubt a perfectly legitimate sense, we ought to say that 
in the case of some arguments a relation of probability does not 
exist, and not that it is unknown. For it is not this probability 


that we have discovered, when the accession of new evidence 
makes it possible to frame a numerical estimate. 

Possibly this theory of unknown probabilities may also gain 
strength from our practice of estimating arguments, which, as 
I maintain, have no numerical value, by reference to those that 
have. We frame two ideal arguments, that is to say, in which 
the general character of the evidence largely resembles what is 
actually within our knowledge, but which is so constituted as 
to yield a numerical value, and we judge that the probability of 
the actual argument lies between these two. Since our standards, 
therefore, are referred to numerical measures in many cases 
where actual measurement is impossible, and since the probability 
lies between two numerical measures, we come to believe that it 
must also, if only we knew it, possess such a measure itself. 

12. To say, then, that a probability is unknown ought to 
mean that it is unknown to us through our lack of skill in arguing 
from given evidence. The evidence justifies a certain degree of 
knowledge, but the weakness of OUT reasoning power prevents our 
knowing what this degree is. At the best, in such cases, we only 
know vaguely with what degree of probability the premisses invest 
the conclusion. That probabilities can bo unknown in this sense 
or known with less distinctness than the argument justifies, 
is clearly the case. We can through stupidity fail to make any 
estimate of a probability at all, just as we may through the 
same cause estimate a probability wrongly. As soon as we 
distinguish between the degree of belief which it is rational to 
entertain and the degree of belief actually entertained, wo have 
in effect admitted that the true probability is not known to 

But this admission must not be allowed to carry us too far. 
Probability is, vide Chapter II. ( 12), relative in a sense to the 
principles of human reason. The degree of probability, which 
it is rational for us to entertain, does not presume perfect logical 
insight, and is relative in part to the secondary propositions 
which we in fact know ; and it is not dependent upon whether 
more perfect logical insight is or is not conceivable. It is the 
degree of probability to which those logical processes lead, of 
which our minds are capable ; or, in the language of Chapter II., 
which those secondary propositions justify, which we in fact know. 
If we do not take this view of probability, if we do not limit it 


in this way and make it, to this extent, relative to human 
powers, we are altogether adrift in the unknown ; for we cannot 
ever know what degree of probability would be justified by the 
perception of logical relations which we are, and must always be, 
incapable of comprehending. 

13. Those who have maintained that, where we cannot assign 
a numerical probability, this is not because there is none, but 
simply because we do not know it, have really meant, I feel 
sure, that with some addition to our knowledge a numerical 
value would be assignable, that is to say that our conclusions 
would have a numerical probability relative to slightly different 
premisses. Unless, therefore, the reader clings to the opinion 
that, in every one of the instances I have cited in the earlier 
paragraphs of this chapter, it is theoretically possible on that 
evidence to assign a numerical value to the probability, we are 
left with the first two of the alternatives of 10, which were 
as follows : either in some cases there is no probability at all ; 
or probabilities do not all belong to a single set of magnitudes 
measurable in terms of a common unit. It would be difficult to 
maintain that there is no logical relation whatever between 
our premiss and our conclusion in those cases where we cannot 
assign a numerical value to the probability ; and if this is so, 
it is really a question of whether the logical relation has char- 
acteristics, other than mensurability, of a kind to justify us in 
calling it a probability-relation. "Which of the two we favour is, 
therefore, partly a matter of definition. We might, that is to 
say, pick out from, probabilities (in the widest sense) a set, if there 
is one, all of which are measurable in terms of a common unit, 
and call the members of this set, and them only, probabilities (in 
the narrow sense). To restrict the term * probability ' in this 
way would be, I think, very inconvenient. For it is possible, 
as I shall show, to find several sets, the members of each of 
which are measurable in terms of a unit common to all the 
members of that set; so that it would be in some degree 
arbitrary 1 which we chose. Further, the distinction between 
probabilities, which would be thus measurable and those which 
would not, is not fundamental. 

At aay rate I aim here at dealing with probability in its 

1 Not altogether ; for it would be natural to select the set to which the 
relation of certainty belongs. 



widest sense, and am averse to confining its scope to a limited 
type of argument. If the opinion that not all probabilities can 
be measured seems paradoxical, it may be due to this divergence 
from a usage which the reader may expect. Common usage, 
even if it involves, as a rule, a flavour of numerical measurement, 
does not consistently exclude those probabilities which are in- 
capable of it. The confused attempts, which have been made, 
to deal with numerically indeterminate probabilities under the 
title of unknown probabilities, show how difficult it is to 
confine the discussion within the intended limits, if the original 
definition is too narrow. 

14. I maintain, then, in what follows, that there are some pairs 
of probabilities between the members of which no comparison 
of magnitude is possible ; that we can say, nevertheless, of some 
pairs of relations of probability that the one is greater and the 
other less, although it is not possible to measure the difference 
between them ; and that in a very special type of case, to be 
dealt with later, a meaning can be given to a numerical comparison 
of magnitude. I think that the results of observation, of which 
examples have been given earlier in this chapter, arc consistent 
with this account. 

By saying that not all probabilities are measurable, I mean 
that it is not possible to say of every pair of conclusions, about 
which we have some knowledge, that the degree of our rational 
belief in one bears any numerical relation to the degree of our 
rational belief in the other ; and by saying that not all proba- 
bilities are comparable in respect of more and less, I mean that 
it is not always possible to say that the degree of our rational 
belief in one conclusion is either equal to, greater than, or less 
than the degree of our belief in another. 

We must now examine a philosophical theory of the quanti- 
tative properties of probability, which would explain and 
justify the conclusions, which reflection discovers, if the preceding 
discussion is correct, in the practice of ordinary argument. We 
must bear in mind that our theory must apply to all probabilities 
and not to a limited class only, and that, as we do not adopt a 
definition of probability which presupposes its numerical men- 
surability, we cannot directly argue from differences in degree 
to a numerical measurement of these differences. The problem 
is subtle and difficult, and the following solution is, therefore, 


proposed with hesitation ; but I am strongly convinced that 
something resembling the conclusion here set forth is true. 

15. The so-called magnitudes or degrees of knowledge or 
probability, in virtue of which one is greater and another less, 
really arise out of an order in which it is possible to place them. 
Certainty, impossibility, and a probability, which has an inter- 
mediate value, for example, constitute an ordered series in which 
the probability lies between certainty and impossibility. In the 
same way there may exist a second probability which Hes between 
certainty and the first probability. When, therefore, we say that 
one probability is greater than another, this precisely means that 
the degree of our rational belief in the first case lies between 
certainty and the degree of our rational belief in the second case. 

On this theory it is easy to see why comparisons of more 
and less are not always possible. They exist between two proba- 
bilities, only when they and certainty all lie on the same ordered 
series. But if more than one distinct series of probabilities 
exist, then it is clear that only those, which belong to the same 
series, can be compared. If the attribute e greater J as applied 
to one of two terms arises solely out of the relative order of the 
terms in a series, then comparisons of greater and less must 
always be possible between terms which are members of the 
same series, and can never be possible between two terms which 
are not members of the same series. Some probabilities are not 
comparable in respect of more and less, because there exists 
more than one path, so to speak, between proof and disproof, 
between certainty and impossibility ; and neither of two proba- 
bilities, which lie on independent paths, bears to the other and 
to certainty the relation of ' between ' which is necessary for 
quantitative comparison. 

If we are comparing the probabilities of two arguments, 
where the conclusion is the same in both and the evidence of 
one exceeds the evidence of the other by the inclusion of some 
fact which is favourably relevant, in such a case a relation seems 
clearly to exist between the two in virtue of which one lies 
nearer to certainty than the other. Several types of argument 
can be instanced in which the existence of such a relation is 
equally apparent. But we cannot assume its presence in every 
case or in comparing in respect of more and less the probabilities 
of every pair of arguments. 


16. Analogous instances are by no means rare, in which, by a 
convenient looseness, the phraseology of quantity is misapplied 
in the same manner as in the case of probability. The simplest 
example is that of colour. When we describe the colour of 
one object as bluer than that of another, or say that it has more 
green in it, we do not mean that there are quantities blue and 
green of which the object's colour possesses more or less ; we 
mean that the colour has a certain position in an order of colours 
and that it is nearer some standard colour than is the colour 
with which we compare it. 

Another example is afforded by the cardinal numbers. We 
say that the number three is greater than the number two, but 
we do not mean that these numbers are quantities one of which 
possesses a greater magnitude than the other. The one is 
greater than the other by reason of its position in the order of 
numbers ; it is further distant from the origin zero. One number 
is greater than another if the second number lies between zero 
and the first. 

But the closest analogy is that of similarity. When we say 
of three objects A, B, and C that B is more like A than C is, we 
mean, not that there is any respect in which B is in itself quan- 
titatively greater than C, but that, if the three objects arc placed 
in an order of similarity, B is nearer to A than is. There are 
also, as in the case of probability, different orders of similarity. 
For instance, a book bound in blue morocco is more like a book 
bound in red morocco than if it were bound in blue calf ; and a 
book bound in red calf is more like the book in red morocco than 
if it were in blue calf. But there may be no comparison between 
the degree of similarity which exists between books bound in 
red morocco and blue morocco, and that which exists between 
books bound in red morocco and red calf. This illustration 
deserves special attention, as the analogy between orders of 
similarity and probability is so great that its apprehension will 
greatly assist that of the ideas I wish to convey. We say 
that one argument is more probable than another (i.e. nearer to 
certainty) in the same kind of way as we can describe one object 
as more like than another to a standard object ui comparison* 

17. Nothing has been said up to this point which boars on 
the question whether probabilities are ever capable of numerical 
comparison. It is true of some types of ordered series that 


there are measurable relations of distance between their members 
as well as order, and that the relation of one of its members 
to an * origin ' can be numerically compared with the relation 
of another member to the same origin. But the legitimacy of 
such comparisons must be matter for special enquiry in each 

It will not be possible to explain in detail how and in what 
sense a meaning can sometimes be given to the numerical measure- 
ment of probabilities until Part II. is reached. But this chapter 
will be more complete if I indicate briefly the conclusions at 
which we shall arrive later. It will be shown that a process 
of compounding probabilities can be defined with such properties 
that it can be conveniently called a process of addition. It will 
sometimes be the case, therefore, that we can say that one 
probability C is equal to the sum of two other probabilities A 
and B, i.e. C = A + B. If in such a case A and B are equal, then 
we may write this C = 2A and say that C is double A. Similarly 
if D = + A, we may write D = 3 A, and so on. We can attach a 
meaning, therefore, to the equation P = ^.A, where P and A are 
relations of probability, and n is a number. The relation of 
certainty has been commonly taken as the unit of such con- 
ventional measurements. Hence if P represents certainty, 
we should say, in ordinary language, that the magnitude of the 
probability A is i. It will be shown also that we can define a 
process, applicable to probabilities, which has the properties of 
arithmetical multiplication. Where numerical measurement is 
possible, we can in consequence perform algebraical operations 
of considerable complexity. The attention, out of proportion 
to their real importance, which has been paid, on account of the 
opportunities of mathematical manipulation which they afford, 
to the limited c}ass of numerical probabilities, seems to be 
a part explanation of the belief, which it is the principal object 
of this chapter to prove erroneous, that all probabilities must 
belong to it. 

J.8. We must look, then, at the quantitative characteristics of 
probability in the following way. Some sets of probabilities 
we can place in an ordered series, in which we can say of any 
pair that one is nearer than the other to certainty, that the 
argument in one case is nearer proof than in the other, and that 
more reason for one conclusion than for the other. But 


we can only build up these ordered series in special cases. If we 
are given two distinct arguments, then 4 , is no general presump- 
tion that their two probabilities and certainty can be placed 
in an order. The burden of establishing the existence of such 
an order lies on us in each separate case. An endeavour will 
be made later to explain in a systematic way how and in 
what circumstances such orders can bo established. The 
argument for the theory here proposed will then be strengthened. 
For the present it has been shown to be agreeable to common 
sense to suppose that an order exists in some cases and not in 

19. Some of the principal properties of ordered series of 
probabilities are as follows : 

(i.) Every probability lies on a path between impossibility 
and certainty ; it is always true to say of a degree 
of probability, which is not identical either with 
impossibility or , witli certainty, that it lies between 
them. Thus certainty, impossibility and any other 
degree of probability form an ordered series. This 
is the same thing as to say that every argument 
amounts to proof, or disproof, or occupies an inter- 
mediate position. 

(ii) A path or series, composed of degrees of probability, 
is not in general compact. It is not ticcesBarily true, 
that is to say, that any pair of probabilities in the 
same series have a probability between them. 

(iii.) The same degree of probability can lie on more than 
one path (i.e. can belong to more than one series). 
Hence, if B lies between A and C, and also lies between 
A' and C', it does not follow that of A and A' either lies 
between the other and certainty. he fact, that the 
same probability can belong to more than one distinct 
series, has its analogy in the case of similarity. 

(iv.) If ABC forms an ordered series, B lying between A 
and C, and BCD forms an ordered series, C lying between 
B and D, then ABCD forms an ordered series, B lying 
between A and D. 

20. The different series of probabilities and their mutual rela- 
tions can be most easily pictured by means of a diagram. Let us 
represent an ordered series by points lying upon a path, alHlk 


points on a given path belonging to the same series. It follows 
from (i.) that the points and I, representing the relations of 
impossibility and certainty, lie on every path, and that all paths 
lie wholly between these points. It follows from (iv.) that the 
same point can lie on more than one path. It is possible, there- 
fore, for paths to intersect and cross. It follows from (iv.) that 
the probability represented by a given point is greater than that 
represented by any other point which can be reached by passing 
along a path with a motion constantly towards the point of 
impossibility, and less than that represented by any point which 
can be reached by moving along a path towards the point of 
certainty. As there are independent paths there will be some 
pairs of points representing relations of probability such that we 
cannot reach one by moving from the other along a path always 
in the same direction. 

These properties are illustrated in the annexed diagram. 
represents impossibility, I certainty, and A a numerically 
measurable probability inter- 
mediate between and I ; U, 
V, W, X, Y, Z are non-numerical 
probabilities, of which, however, 
V is less than the numerical 
probability A, and is also less 
than W, X, and Y. X and Y 
are both greater than W, and greater than V, but are not 
comparable with one another, or with A. V and Z are both 
less than W, X, and Y, but are not comparable with one 
another ; U is not quantitatively comparable with any of the 
probabilities V, W, X, Y, Z. Probabilities which are numerically 
comparable will all belong to one series, and the path of this 
series, which we may call the numerical path or strand, will be 
represented by OAI. 

21. The chief results which have been reached so far are 
collected together below, and expressed with precision : 

(i.) There are amongst degrees of probability or rational 
belief various sets, each set composing an ordered 
series. These series are ordered by virtue of a relation 
of ' between/ If B is ' between ' A and 0, ABC form a 
(ii.) There are two degrees of probability and I between 


which all other probabilities lie. If, that is to say, A 
is a probability, OAI form a series. O represents im- 
possibility and I certainty, 
(iii.) II A lies between and B, we may write this AB, 

so that OA and AI are true for all probabilities. 

(iv.) If AB, the probability B is said to be greater than 

the probability A, and this can be expressed by B>A. 

(v.) If the conclusion a bears the relation of probability 

P to the premiss 7^, or if, in other words, the hypothesis 

h invests the conclusion a with probability P, this may 

be written aPh. It may also be written a/7i=P. 

This latter expression, which proves to be the more useful of the 

two for most purposes, is of fundamental importance. If dPJi 

and a'Pk', i.e. if the probability of a relative to h is the 

same as the probability of of relative to Ji' y this may be written 

a/h=a' '/h'. The value of the symbol a/h, which represents 

what is called by other writers ' the probability of a/ lies in 

the fact that it contains explicit reference to the data to which 

the probability relates the conclusion, and avoids the numerous 

errors which have arisen out of the omission of this reference. 



ABSOLUTE. * Sure, Sir, this is not very reasonable, to summon my affection 

for a lady I know nothing of.' 
SIR ANTHONY. s I am sure, Sir, 'tis more unreasonable in you to object 

to a lady you know nothing of.' 1 

1. IN the last chapter it was assumed that in some cases the 
probabilities of two arguments may be equal. It was also argued 
that there are other cases in which one probability is, in some 
sense, greater than another. But so far there has been nothing 
to show how we are to know when two probabilities are equal or 
unequal. The recognition of equality, when it exists, will be 
dealt with in this chapter, and the recognition of inequality in 
the next. An historical account of the various theories about 
this problem, which have been held from time to time, will be 
given in Chapter VII. 

2. The determination of equality between probabilities has 
received hitherto much more attention than the determination 
of inequality. This has been due to the stress which has been 
laid on the mathematical side of the subject. In order that 
numerical measurement may be possible, we must be given a 
number of equally probable alternatives. The discovery of a 
rule, by which equiprobability could be established, was, there- 
fore, essential. A rule, adequate to the purpose, introduced by 
James Bernoulli, who was the real founder of mathematical 
probability, 2 has been widely adopted, generally under the 
title of The Principle of Non-Sufficient Reason, down to the 
present time. This description is clumsy and unsatisfactory, 
and, if it is justifiable to break away from tradition, I prefer to 
call it The Principle of Indifference. 

7 - Quoted by Mr. Bosanquet with reference to the Principle of Non-Sufficient 
Beason. a See also Chap. "VXC. 



The Principle of Indifference asserts that if there is no known 
reason for predicating of our subject one rather than another of 
several alternatives, then relatively to such knowledge the 
assertions of each of these alternatives have an equal probability. 
Thus equal probabilities must be assigned to each of several 
arguments, if there is an absence of positive ground for assigning 
unequal ones. 

This rule, as it stands, may lead to paradoxical and even 
contradictory conclusions. I propose to criticise it in detail, 
and then to consider whether any valid modification of it is 
discoverable. For several of the criticisms which follow I am 
much indebted to Von Kries's Die Principien der Walirscliein- 

3. If every probability was necessarily either greater than, 
equal to, or less than any other, the Principle of Indifference 
would be plausible. For if the evidence affords no ground for 
attributing unequal probabilities to the alternative predications, 
it seems to follow that they must be equal. If, on the other hand, 
there need be neither equality nor inequality between, prob- 
abilities, this method of reasoning fails. Apart, however, from 
this objection, which is based orx the arguments of Chapter III., 
the plausibility of the principle will be most easily shaken by an 
exhibition of the contradictions which it involves. These fall 
under three or four distinct heads. In 4-9 my criticism will 
be purely destructive, and I shall not attempt in these paragraphs 
to indicate my own way out of the difficulties. 

4. Consider a proposition, about the subject of which we know 
only the meaning, and about the truth of which, as applied to 
this subject, we possess no external relevant evidence. It has 
been held that there are here two exhaustive and exclusive 
alternatives the truth of the proposition and the truth of its 
contradictory while our knowledge of the subject affords no 
ground for preferring one to the other. Thus if a and a are 
contradictories, about the subject of which we have no outside 
knowledge, it is inferred that the probability of each is J. a In 

1 Published in 1886. A brief account of Von Kries's principal conclusions 
will be given on p. 87. A useful summary of his book will be found in a review 
by Meinong, published in the Gdttingische gekhrte Anzeigen for 1890 (pp. 56-75). 

a Cf. (e.<7.) the well-known passage in Jcvons's Principles of Science, voi i. 
p. 243, in which he assigns the probability J to the proposition " A Platythhptio 
Coefficient is positive." Jevons points out, by way of proof, that no other 


the same way the probabilities of two other propositions, 6 and c, 
having the same subject as a, may be each . But without 
having any evidence bearing on the subject of these propositions 
we may know that the predicates are contraries amongst them- 
selves, and, therefore, exclusive alternatives a supposition which 
leads by means of the same principle to values inconsistent with 
those just obtained. If, for instance, having no evidence relevant 
to the colour of this book, we could conclude that J is the proba- 
bility of * This book is red,' we could conclude equally that the 
probability of each of the propositions ' This book is black ' and 
' This book is blue ' is also j- So that we are faced with the 
impossible case of three exclusive alternatives all as likely as not. 
A defender of the Principle of Indifference might rejoin that we 
are assuming knowledge of the proposition : e Two different 
colours cannot be predicated of the same subject at the same 
time J ; and that, if we know this, it constitutes relevant out- 
side evidence. But such evidence is about the predicate, not 
about the subject. Thus the defender of the Principle will be 
driven on, either to confine it to cases where we know nothing 
about either the subject or the predicate, which would be to 
emasculate it for all practical purposes, or else to revise and 
amplify it, which is what we propose to do ourselves. 

The difficulty cannot be met by saying that we must know 
and take account of the number of possible contraries. For the 
number of contraries to any proposition on any evidence is always 
infinite ; ah is contrary to a for all values of 6. The same point 
can be put in a form which does not involve contraries or 
contradictories. For example, a/h~ J and a&/&=, if A is 

probability could reasonably be given. This, of course, involves the assumption 
that every proposition must have some numerical probability. Such a con- 
tention was first criticised, so far as I am aware, by Bishop Terrot in the Edin. 
Phil. Trans, for 1856. It was deliberately rejected by Boole in his last pub- 
lished work on probability : " It is a plain consequence," he says (JSdin. Phil. 
Trans, vol. xxi. p. 624), " of the logical theory of probabilities, that the state 
of expectation, which accompanies entire ignorance of an event is properly 
represented, not by the fraction J, but by the indefinite form #." Jevons's 
particular example, however, is also open to the objection that we do not even 
know the meaning of the subject of the proposition. Would he maintain that 
there is any sense in saying that for those who know no Arabic the probability 
of every statement expressed in Arabic is even ? How far has he been 
influenced in the choice of his example by known characteristics of the predicate 

* positive ' ? Would he have assigned the probability to the proposition 

* A Platythliptic Coefficient is a perfect cube ' ? What about the proposition 
' A Platythliptic Coefficient is allogeneous ' ? 


irrelevant both to a and to &, in the sense required by the crude 
Principle of Indifference. 1 It follows from this that, if a is true, 
b must be true also. If it follows from the absence of positive 
data that c A is a red book' has a probability of J, and that the 
probability of * A is red ' is also , then we may deduce that, if 
A is red, it must certainly be a book. 

We may take it, then, that the probability of a proposition, 
about the subject of which we have no extraneous evidence, is 
not necessarily . Whether or not this conclusion discredits the 
Principle of Indifference, it is important on its own account, and 
will help later on to confute some famous conclusions of Laplace's 

5. Objection can now be made in a somewhat different shape. 
Let us suppose as before that there is no positive evidence relating 
to the subjects of the propositions under examination which 
would lead us to discriminate in any way between certain 
alternative predicates. If, to take an example, we have no 
information whatever as to the area or population of the 
countries of the world, a man is as likely to be an inhabitant 
of Great Britain as of France, there being no reason to prefer 
one alternative to the other. 2 He is also as likely to be an 
inhabitant of Ireland as of France. And on the same principle 
he is as likely to be an inhabitant of the British Isles as of 
France. And yet these conclusions are plainly inconsistent. 
For our first two propositions together yield the conclusion 
that he is twice as likely to be an inhabitant of the British 
Isles as of France. 

Unless we argue, as I do not think we can, that the knowledge 
that the British Isles are composed of Great Britain and Ireland 
is a ground for supposing that a man is more likely to inhabit 
them than France, there is no way .out of the contradiction. It 
is not plausible to maintain, when we are considering the relative 
populations of different areas, that the number of names of sub- 
divisions which are within our knowledge, is, in the absence of 
any evidence as to their sise, a piece of relevant evidence. 

At any rate, many other similar examples could be invented, 

1 a/h stands for * the probability of a on hypothesis A.' 

2 This example raises a difficulty similar to that raised by Von Kries's 
example of the meteor. Stumpf has propounded an invalid solution of Von 
Kries's difficulty. Against the example proposed here, Stumpf s solution has 
less plausibility than against Von Kries's. 


which would require a special explanation in each case ; for the 
above is an instance of a perfectly general difficulty. The 
possible alternatives may be a, b, c, and d, and there may be no 
means of discriminating between them ; but equally there may 
be no means of discriminating between (a or 6), c, and d. 
This difficulty could be made striking in a variety of ways, but 
it will be better to criticise the principle further from a some- 
what different side. 

6. Consider the specific volume of a given substance. 1 Let us 
suppose that we know the specific volume to lie between 1 and 3, 
but that we have no information as to whereabouts in this interval 
its exact value is to be found. The Principle of Indifference 
would allow us to assume that it is as likely to lie between 1 and 
2 as between 2 and 3 ; for there is no reason for supposing that it 
lies in one interval rather than in the other. But now consider 
the specific density. The specific density is the reciprocal of 
the specific volume, so that if the latter is v the former is \. 
Our data remaining as before, we know that the specific density 
must lie between 1 and -J, and, by the same i;se of the Principle 
of Indifference as before, that it is as likely to lie between 
1 and f as between f and \. But the specific volume being 
a determinate function of the specific density, if the latter lies 
between 1 and f, the former lies between 1 and 1J, and if the 
latter lies between f and J, the former lies between 1J and 3. 
It follows, therefore, that the specific volume is as likely to lie 
between 1 and 1 J as between 1 J and 3 ; whereas we have akeady 
proved, relatively to precisely the same data, that it is as likely 
to lie between 1 and 2 as between 2 and 3. Moreover, any other 
function of the specific volume would have suited our purpose 
equally well, and by a suitable choice of this function we might 
have proved in a similar manner that any division whatever 
of the interval 1 to 3 yields sub-intervals of equal probability. 
Specific volume and specific density are simply alternative 
methods of measuring the same objective quantity ; and there 
are many methods which might be adopted, each yielding on the 
application of the Principle of Indifference a different probability 
for a given objective variation in the quantity. 2 

1 This example is taken from Von Kries, op. cit. p. 24. Von Kries does 
not seem to me to explain correctly how the contradiction arises. 

a A. Nitsche (** Die Dimeusionen der Wahrsoheinlichkeit und die Evidenz der 
Ungewissheit," Vierteljahrsschr. /. wissensck. Philos. vol xvi. p. 29, 1392), in 


The arbitrary nature of particular methods of measurement 
of this and of many other physical quantities is easily explained. 
The objective quality measured may not, strictly speaking, possess 
numerical quantitativeness, although it has the properties neces- 
sary for measurement by means of correlation with numbers. 
The values which it can assume may be capable of being 
ranged in an order, and it will sometimes happen that the series 
which is thus formed is continuous, so that a value can always 
be found whose order in the series is between any two selected 
values ; but it does not follow from this that there is any meaning 
in the assertion that one value is twice another value. The 
relations of continuous order can exist between the terms of a 
series of values, without the relations of numerical quantitative- 
ness necessarily existing also, and in such cases we can adopt a 
largely arbitrary measure of the successive terms, which yields 
results which may be satisfactory for many purposes, those, 
for instance, of mathematical physics, though not for those of 
probability. This method is to select some other series of 
quantities or numbers, each of the terms of which corresponds 
in order to one and only one of the terms of the series which 
we wish to measure, For instance, the series of character- 
istics, differing in degree, which are measured by specific 
volume, have this relation to the series of numerical ratios 
between the volumes of equal masses of the substances, the 
specific volumes of which are in question, and of water. They 
have it also to the corresponding ratios which give rise to the 
measure of specific density. But these only yield conventional 
measurements, and the numbers with which we correlate the 

criticising Von Krios, argues that the alternatives to which tho principle must 
be applied aro the smallest ^physically distinguishable intervals, and that tho 
probability of tho specific volume's lying within a certain rango of values turns 
on tho number of such distinguishable intervals in tho range. This procedure 
might conceivably provide the correct method of computation, but it does not 
therefore restore the credit of the Principle of Indifference. For it is argued, 
not that the results of applying the principle are always wrong, but that it does 
not lead unambiguously to tho correct procedure. If wo do not know tho 
number of distinguishable intervals wo have no reason for supposing that tho 
specific volume lies between 1 and 2 rather than 2 and 3, and tho principle can 
therefore be applied as it has been applied above. And even if we do know 
the number and reckon intervals as equal which contain an equal number of 
* physically distinguishable ' parts, is it certain that this does not simply 
provide us with a now system of measurement, which has the same conven- 
tional basis as the methods of specific volume and specific density, and ia no 
more the ono correct measure than those aro ? 


terms which, we wish to measure can be selected in a variety of 
ways. It follows that equal intervals between the numbers 
which represent the ratios do not necessarily correspond to equal 
intervals between the qualities under measurement ; for these 
numerical differences depend upon which convention of measure- 
ment we have selected. 

7. A somewhat analogous difficulty arises in connection with 
the problems of what is known as ' geometrical ' or * local * 
probability. 1 In these problems we are concerned with the posi- 
tion of a point or infinitesimal area or volume within a con- 
tinuum. 2 The number of cases here is indefinite, but the Principle 
of Indifference has been held to justify the supposition that equal 
lengths or areas or volumes of the continuum are, in the absence 
of discriminating evidence, equally likely to contain the point. 
It has long been known that this assumption leads in numerous, 
cases to contradictory conclusions. If, for instance, two points 
A and A' are taken at random on the surface of a sphere, and we 
seek the probability that the lesser of the two arcs of the great 
circle AA' is less than a, we get one result by assuming that the 
probability of a point's lying on a given portion of the sphere's 
surface is proportional to the area of that portion, and another 
result by assuming that, if a point lies on a given great circle, the 
probability of its lying on a given arc of that circle is proportional 
to the length of the arc, each of these assumptions being equally 
justified by the Principle of Indifference. 

Or consider the following problem : if a chord in a circle is 
drawn at random, what is the probability that it will be less 
than the side of the inscribed equilateral triangle. One can 
argue : 

(a) It is indifferent at what point one end of the chord lies* 
If we suppose this end fixed, the direction is then 

1 The best accounts of this subject are to be found in Czuber, Qeometrische 
Wahrscheinlichkeiten und Mittelwerte; Czuber, Wahrscheinlichkeiterechnung, 
vol. i. pp. 75-109; Crofton, Encycl. Brit. (9th edit.), article 'Probability'; 
Borel, ElimenU de la ih&orie des probability, chaps. vi.-viii. ; a few other 
references are given in the following pages, and a number of discussions of 
individual problems will be found in the mathematical volumes of the 
Educational Times. The interest of the subject is primarily mathematical, 
and no discussion of its principal problems will be attempted here. 

2 As Czuber points out ( W ahrscheirilichbeitsrechnung, vol. i. p. 84), all 
problems, whether geometrical or arithmetical, which deal with a continuum 
and with non-enumerable aggregates, are commonly discussed under the name of 
' geometrical probability.' See also Lammel, Unterwchungen. 


chosen at random. In this case the answer is easily 
shown to he f . 

(6) It is indifferent in what direction we suppose the chord 
to lie. Beginning with this apparently not less justifi- 
able assumption, we find that the answer is . 
(c) To choose a chord at random, one must choose its 
middle point at random. If the chord is to be less 
than the side of the inscribed equilateral triangle, the 
middle point must be at a greater distance from the 
centre than half the radius. But the area at a 
greater distance than this is J of the whole. Hence 
our answer is -. 1 

In general, if x and f(x) are both continuous variables, varying 
always in the same or in the opposite sense, and x must lie 
between a and 6, then the probability that x lies between c 

d o 
and d, where a<c<d<b, seems to be , 'and the probability 

""* d/ 

that f(x) lies between /(c) and f(d) to bo ' ;,,, _ '>v These 

expressions, which represent the probabilities of necessarily 
concordant conclusions, are not, as they ought to be, equal 2 

8. More than one attempt has been made to separate the 
cases in which the Principle of Indifference can be legitimately 
applied to examples of geometrical probability from thoso in 
which it cannot. M. Borcl argues that the mathematician can 
define the geometrical probability that a point M lies on a certain 
segment PQ of AD as proportional to the length of the segment, 
but that this definition is conventional until its consequences 
have been confirmed d posteriori by their conformity with the 
results of empirical observation. He points out that in actual 
cases there are generally some considerations present which 
lead us to prefer one of the possible assumptions to the others* 
Whether or not this is so, the proposed procedure amounts to 
aix abandonment of the Principle of Indifference as a valid 
criterion, and leaves our choice undetermined when further 
evidence is not forthcoming. 

M. Poincar<, who also held that judgments of equiprobability 
in such cases depend upon a c convention/ endeavoured to mini- 

1 Bertrand, Calcul des yrobobititis, p. 6. 
3 Sec ( Borel, Moments de la theorie des probability, p. 85. 


mise the importance of the arbitrary element by showing that, 
under certain conditions, the result is independent of the particu- 
lar convention which is chosen. Instead of assuming that the 
point is equally likely to lie in every infinitesimal interval dx 
we may represent the probability of its lying in this interval by 
the function <fr(x)dx. M. Poiacare showed that, in the game of 
rouge et noir, for instance, where we have a number of compart- 
ments arranged in a circle coloured alternately black and white, 
if we can assume that <p(x) is a regular function, continuous and 
with continuous differential coefficients, then, whatever the 
particular form of the function, the probability of black is 
approximately equal to that of white, 1 

Whether or not investigations on these lines prove to have 
a practical value, they have not, I think, any theoretical import- 
ance. If, as I maintain, the probability cf>(x) is not necessarily 
numerical, it is not a generally justifiable assumption to 
take its continuity for granted. We have, in the particular 
example quoted, a number of alternatives, half of which lead to 
black and half to white ; the assumption of continuity amounts 
to the assumption that for every white alternative there is a 
black alternative whose probability is very nearly equal to that 
of the white. Naturally in such a case we can get an approxi- 
mately equal probability for the whites as a whole and for the 
blacks as a whole, without assuming equal probability for each 
alternative individually. But this fact has no bearing on the 
theoretical difficulties which we are discussing. 

M. Bertrand is so much impressed by the contradictions of 
geometrical probability that he wishes to exclude all examples 
in which the number of alternatives is infinite. 2 It will be argued 
in the sequel that something resembling this is true. The dis- 
cussion of this question will be resumed in 21-25. 

9. There is yet another group of cases, distinct hi character 
from those considered so far, in which the principle does not 
seem to provide us with unambiguous guidance. The typical 
example is that of an urn containing black and white balls in an 

1 Poincare', Calcul des probability, pp. 126 et seg[. 

2 Bertrand, Oalcul des probability p. 4: "L'infini n'est pas un nombre; 
on ne doit pas, sans explication, Fintroduire dans les raisonnements. La 
precision illusoire des mots pourrait faire naitre des contradictions. Choisir 
au hasard, entre un nombre Tnfi-ni de cas possibles, n'est pas une indication 



unknown proportion. 1 The Principle of Indifference can 'b( 
claimed to support the most usual hypothesis, namely, that all 
possible numerical ratios of black and white are equally probable. 
But we might equally well assume that all possible constitutions 2 
of the system of balls are equally probable, so that each individual 
ball is assumed equally likely to be black or white. It would 
follow from this that an approximately equal number of black 
and white balls is more probable than a large excess of one colour. 
On this hypothesis, moreover, the drawing of one ball and the 
resulting knowledge of its colour leaves unaltered the proba- 
bilities of the various possible constitutions of the rest of the bag ; 
whereas on the first hypothesis knowledge of the colour of one 
ball, drawn and not replaced, manifestly alters the probability 
of the colour of the next ball to be drawn. Either of these hypo- 
theses seems to satisfy the Principle, of Indifference, .and a believer 
in the absolute validity of the principle will doubtless adopt that 
one which enters his mind first. 3 

The same point is very clearly illustrated by an example 
which I take from Von Kries. Two cards, chosen from different 
packs, are placed face downwards on the table ; one is taken 
up and found to be of a black suit : what is the chance that the 
other is black also ? One would naturally reply that the 
chance is even. But this is based on the supposition, relatively 
unpopular with writers on the subject, that every ' constitution ' 
is equally probable, i.e. that each individual card is as likely 
to be black as red. If we prefer this assumption, we must relin- 

1 The difficulty in question was first pointed out by Boole, Laws of Thought* 
pp. 369-370. After discussing the Law of Succession, Boole proceeds to show 
that "there are other hypotheses, as strictly involving the principle of the 
6 equal distribution of knowledge or ignorance * which would also conduct to 
conflicting results." See also Von Kries, op. tit, pp. 31-34, 59, and Stumpf, 
Uber den Begriff der mathematischen Wahrscheinlicfikeit, Bavarian Academy, 
1892, pp. 64-68. 

a If A and B are two balls, A white, B black, and A black, B white, arc 
different * constitutions.' But if we consider different numerical ratios, those 
two cases are indistinguishable, and count as one only. 

3 0. S. Peirce in his Theory of Probable Inference (Johns Hopkins Studies in 
Logic), pp. 172, 173, argues that the ' constitution * hypothesis is alone valid, 
on the ground that, of the two hypotheses, only this one is consistent with itself. 
I agree with his conclusion, and shall give at the close of the chapter the funda- 
mental considerations which lead to the rejection of the ' ratio ' hypothesis. 
Stumpf points out that the probability of drawing a white ball is, in any 
case, J. This is true ; but the probability of a second white clearly depends 
upon which of the two hypotheses has been preferred. Nitsche (loo. cti. p. 31) 
seems to miss the point of the difficulty in the same way. 


|uish the text-book theory that the drawing of a black ball from 
an urn, containing black and white balls in unknown proportions, 
affects our knowledge as to the proportion of black and white 
amongst the remaining balls. 

The alternative or text-booktheory assumes that there 
are three equal possibilities one of each colour, both black, both 
red. If both cards are black, we are twice as likely to turn up 
a black card than if only one is black. After we have turned up 
a black, the probability that the other is black is, therefore, twice 
as great as the probability that it is red. The chance of the 
second's being black is therefore f. 1 The Principle of Indifference 
has nothing to say against either solution. Until some further 
criterion has been proposed we seem compelled to agree with 
Poincar6 that a preference for either hypothesis is wholly arbitrary. 

10. Such, then, are the kinds of result to which an unguarded 
use of the Principle of Indifference may lead us. The difficulties, 
to which attention has been drawn, have been noticed before ; 
but the discredit has not been emphatically thrown on the 
original source of error. Yet the principle certainly remains as 
a negative criterion ; two propositions cannot be equally probable, 
so long as there is any ground for discriminating between them. 
The principle is a necessary, but not, as it seems, a sufficient 

The enunciation of some sufficient rule is certainly essential if 
we are to make any progress in the subject. But the difficulty 
of discovering a correct principle is considerable. This difficulty 
is partly responsible, I think, for the doubts which philosophers 
and many others have often felt regarding any practical applica- 
tion of the Calculus. Many candid persons, when confronted 
with the results of Probability, feel a strong sense of the un- 
certainty of the logical basis upon which it seems to rest. It is 
difficult to find an intelligible account of the meaning of c proba- 
bility/ or of how we are ever to determine the probability of any 
particular proposition ; and yet treatises on the subject profess 
to arrive at complicated results of the greatest precision and the 
most profound practical importance. 

The incautious methods and exaggerated claims of the school 
of Laplace have undoubtedly contributed towards the existence 
of these sentiments. But the general scepticism, which I believe 
1 This is Poisson's solution, Reckerches, p. 96. 


to be much more widely spread than tlie literature of tlie subject 
admits, is more fundamental. In this matter Hume need not 
have felt " affrighted and confounded with that forelorn solitude, 
in which I am placed in my philosophy/' or have fancied himself 
" some strange uncouth monster, who not being able to mingle 
and unite in society, has been expelTd all human commerce, 
and left utterly abandon'd and disconsolate." In his views on 
probability, he stands for the plain man against the sophisms 
and ingenuities of " metaphysicians, logicians, mathematicians, 
and even theologians." 

Yet such scepticism goes too far. The judgments of proba- 
bility, upon which we depend for almost all our beliefs in matters 
of experience, undoubtedly depend on a strong psychological 
propensity in us to consider objects in a particular light. But 
this is no ground for supposing that they are nothing more than 
" lively imaginations." The same is true of the judgments in 
virtue of which we assent to other logical arguments ; and yet 
in such cases we believe that there may be present some element 
of objective validity, transcending the psychological impulsion, 
with which primarily we are presented. So also in the case of 
probability, we may believe that our judgments can penetrate 
into the real world, even though their credentials are subjective. 

11. We must now inquire how far it is possible to rehabilitate 
the Principle of Indifference or find a substitute for it. There 
are several distinct difficulties which need attention in a dis- 
cussion of the problems raised in the preceding paragraphs. 
Our first object must be to mate the Principle itself more precise 
by disclosing how far its application is mechanical and how far 
it involves an appeal to logical intuition. 

12. Without compromising the objective character of relations 
of probability, we must nevertheless admit that there is little 
likelihood of our discovering a method of recognising particular 
probabilities, without any assistance whatever from intuition or 
direct judgment. Inasmuch as it is always assumed that we can 
sometimes judge directly that a conclusion follows from a premiss, 
it is no great extension of this assumption to suppose that we 
can sometimes recognise that a conclusion partially follows from, 
or stands in a relation of probability to, a premiss. Moreover, 
the failure to explain or define c probability * in terms of other 
logical notions, creates a presumption that particular relations 


of probability must be, in the first instance, directly recognised 
as such, and cannot be evolved by rule out of data which them- 
selves contain nt> statements of probability. 

On the other hand, although we cannot exclude every element 
of direct judgment, these judgments may be limited and con- 
trolled, perhaps, by logical rules and principles which possess a 
general application. While we may possess a faculty of direct 
recognition of many relations of probability, as in the case of 
many other logical relations, yet some may be much more 
easily recognisable than others. The object of a logical system 
of probability is to enable us to know the relations, which 
cannot be easily perceived, by means of other relations which 
we can recognise more distinctly to convert, in fact, vague 
knowledge into more distinct knowledge. 1 

13. Let us seek to distinguish between the element of direct 
judgment and the element of mechanical rule in the Principle 
of Indifference. The enunciation of this principle, as it is 
ordinarily expressed, cloaks, but does not avoid, the former 
element. It is in part a formula and in part an appeal to direct 
inspection ; but in addition to the obscurity and ambiguity of 
the formula, the appeal to intuition is not as explicit as it should 
be. The principle states that ' there must be no known 
reason for preferring one of a set of alternatives to any other.' 
"What does this mean ? What are * reasons/ and how are 
we to know whether they do or do not justify us in preferring 
one alternative to another ? I do not know any discussion 
of Probability in which this question has been so much as 
asked. If, for example, we are considering the probability 
of drawing a black ball from an urn containing balls which are 

1 As it is the aim of trigonometry to determine the position of an object, 
which is in a aense visible, not by a direct observation of it, but by observing 
some other object together with certain relations, so an indirect method of this 
kind is the aim of all logical system. If the truth of some propositions, and the 
validity of some arguments, could not be recognised directly, we could make no 
progress. We may have, moreover, some power of direct recognition where it 
is not necessary in our logical system that we should make use of it. In these 
cases the method of logical proof increases the certainty of knowledge, which 
we might be able to possess in a more doubtful manner without it. In other 
oases, that, for instance, of a complicated mathematical theorem, it enables 
us to know propositions to be true, which are altogether beyond the reach of 
our direct insight ; just as we can often obtain knowledge about the position 
of a partially visible or even invisible object by starting with observations of 
other objects. 


black and white, we assume that the difference of colour be- 
tween the balls is not a reason for preferring either alternative. 
But how do we know this, unless by a judgment that, on the 
evidence in hand, our knowledge of the colours of the balls is 
irrelevant to the probability in question ? We know of some 
respects in which the alternatives differ ; but we judge that* a 
knowledge of these differences is not relevant. If, on the other 
hand, we were taking the balls out of the urn with a magnet, 
and knew that the black balls were of iron and the white of tin, 
we might regard the fact, that a ball was iron and not tin, as 
very important in determining the probability of its being 
drawn. Before, then, we can begin to apply the Principle of 
Indifference, we must have made a number of direct judgments 
to the effect that the probabilities under consideration are un- 
affected by the inclusion in the evidence of certain particular 
details. We have no right to say of any known difference 
between the two alternatives that it is ' no reason ' for preferring 
one of them, unless we have judged that a knowledge of this 
difference is irrelevant to the probability in question. 

14. A brief digression is now necessary, in order to introduce 
some new terms. There are in general two principal types of 
probabilities, the magnitudes of which we seek to compare, 
those in which the evidence is the same and the conclusions 
different, and those in which the evidence is different but the 
conclusion the same. Other types of comparison may be re- 
quired, but these two are by far the commonest. In the first 
we compare the likelihood of two conclusions on given evidence ; 
in the second we consider what difference a change of evidence 
makes to the likelihood of a given conclusion. In symbolic 
language we may wish to compare x/h with y/h, or x/h with 
x/h-Ji. We may call tie first type judgments of preference, or, 
when there is equality between x/h and y/h, of indifference ; and 
the second type we may call judgments of relevance, or, when there 
is equality between x/h and xjhji, of irrelevance. In' the first 
we consider whether or not x is to be preferred to y on evidence h ; 
in the second we consider whether the addition of h to evidence 
h is relevant to x. 

The Principle of Indifference endeavours to formulate a rule 
which will justify judgments of indifference. But the rule that 
there must be no ground for preferring one alternative to another, 


involves, if it is to be a guiding rule at all, and not a petitio 
principii, an appeal to judgments of irrelevance. 

The simplest definition of Irrelevance is as follows: \ is 
irrelevant to x on evidence h, if the probability of x on evidence Jih^ 
is the same as its probability on evidence h. 1 But for a reason 
which will appear in Chapter VI. 3 a stricter and more complicated 
definition, as follows, is theoretically preferable : Ji is irrelevant 
to x on evidence 7^, if there is no proposition, inferrible from h^h 
but not from h, such that its addition to evidence h affects the 
probability of #. 2 Any proposition which is irrelevant in the 
strict sense is, of course, also irrelevant in the simpler sense ; 
but if we were to adopt the simpler definition,, it would sometimes 
occur that a part of evidence would be relevant, which taken as 
a whole was irrelevant. The more elaborate definition by avoid- 
ing this proves in the sequel more convenient. If the condition 
x/h 1 h=x/h alone is satisfied, we may say that the evidence h{ 
is ' irrelevant as a whole. 5 3 

It will be convenient to define also two other phrases. ^ 
and h 2 are independent and complementary parts of the evidence, 
if between them they make up h and neither can be inferred from 
the other. If x is the conclusion, and \ and h 2 are independent 
and complementary parts of the evidence, then \ is relevant if 
the addition of it to A 2 affects the probability of #. 4 

Some propositions regarding irrelevance will be proved in 
Part II. If x is the contradictory of \ and x^^x/h, then 
x/Kjh^x/h. Thus the contradictory of irrelevant evidence is 
also irrelevant. Also, if x/yh = x/h, it follows that y/xh=y/h. 
Hence if, on initial evidence h, y is irrelevant to x, then, on the 
same initial evidence, x is irrelevant to y y i.e. if in a given state 
of knowledge one occurrence has no bearing on another, then 
equally the second has no bearing on the first. 

15. This distinction enables us to formulate the Principle of 
Indifference at any rate more precisely. There must be no 
relevant evidence relating to one alternative, unless there is 
corresponding evidence relating to the other; our relevant 

1 That is to say, A x is irrelevant to xjh if x/h l h=xlh> 

2 That is to say, 7^ is irrelevant to x/h, if there is no proposition h\ such that 
A'i/A^sl, AyA*!, and x/h'J^x/h. 

3 Where no misunderstanding can arise, the qualification * as a whole ' will 
be sometimes omitted. 

4 I.e (in symbolism) ^ and A 2 are independent and complementary parts of 
h if A^a =A, Ai/Aasjsl, and h^h^l. Also A x is relevant if x/h^x/h^ 


evidence, that is to say, must be symmetrical with regard to the 
alternatives, and must be applicable to each in the same manner. 
This is the rule at which the Principle of Indifference somewhat 
obscurely aims. We must first determine what parts of our 
evidence are relevant on the whole by a series of judgments of rele- 
vance, not easily reduced to rule, of the type described above. 
If this relevant evidence is of the same form for both alternatives, 
then the Principle authorises a judgment of indifference. 

16. This rule can be expressed more precisely in symbolic 
language. Let us assume, to begin with, that the alternative 
conclusions are expressible in the forms $(a) and 0(6), where 
<(#) is a propositional function. 1 The difference between them, 
that is to say, can be represented in terms of a single variable. 

The Principle of Indifference is applicable to the alternatives 
</>(#) and <(&), when the evidence h is so constituted that, if /(a) 
is an independent part of k (see 14) which is relevant to <(a), 
and does not contain any independent parts which are irrelevant 
to <(<$), then h includes /(&) also. 

The rule can be extended by successive steps to cases in 
which we have more than one variable. We can, if the necessary 
conditions are fulfilled, successively compare the probabilities 
of (}>(ci' l cf' 2 ) and ^(bfa), and of 0(& 1 a 3 ) and ^(6 1 & 2 ), and establish 
equality between ^(^ 2 ) and $(1^). 

This elucidation is suited to most of the cases to which the 
Principle of Indifference is ordinarily applied. Thus in the 
favourite examples in which balls are drawn from urns, we can 
infer from our evidence no relevant proposition about white balls, 
such that we cannot infer a corresponding proposition about 
black balls. Most of the examples, to which the mathematical 
theory of chances has been applied, and which depend upon the 
Principle of Indifference, can be arranged, I think, in the forms 
which the rule requires as formulated above. 

17. We can now clear up the difficulties which arose over the 
group of cases dealt with in 9, the typical example of which was 
the problem of the urn containing black and white balls in an 
unknown proportion. This more precise enunciation of the 
Principle enables us to show that of the two solutions the equi- 
probability of each c constitution * is alone legitimate, and the 

1 If 0(0), 0(6), etc., are propositions, and a; is a variable, capable of taking 
;he values a, b, etc., then <j>(x) is a propositional function. 


equiprobability of each numerical ratio erroneous. Let us write 
the alternative c The proportion of black balls is x '==(j>(x), and 
the datum e There are n balls in the bag, with regard to none 
of which it is known whether they are black or white '=A. 
On the ' ratio ' hypothesis it is argued that the Principle of 
Indifference justifies the judgment of indifference, <t>(x)/h = 
4>(y)/h. In order that this may be valid, it must be possible to 
state the relevant evidence in the form f(x) f(y). But this is 
not the case. If #=| and y = J 5 we have relevant knowledge 
about the way in which a proportion of black balls of one half 
can arise, which is not identical with our knowledge of the way 
in which a proportion of one quarter can arise. If there are four 
balls, A, B, C, D, one half are black, if A, B or A, C or A, D or 
B, or B, D or C, D are black ; and one quarter are black, 
if A or B or C or D are black. These propositions are not identical 
in form, and only by a false judgment of irrelevance can we 
ignore them. On the c constitution ' hypothesis, however, 
where A, B black and A, C black are treated as distinct alter- 
natives, this want of symmetry in our relevant evidence cannot 

18. We can also deal with the point which was illustrated by 
the difficulty raised in 4. We considered there the probabilities 
of a and its contradictory a when there is no external evidence 
relevant to either. What exactly do we mean by saying that 
there is no relevant evidence ? Is the addition of the word 
external significant 1 If a represents a particular proposition, 
we must know something about it, namely, its meaning. May 
not the apprehension of its meaning afford us some relevant 
evidence ? If so, such evidence must not be excluded. If, then, 
we say that there is no relevant evidence, we must mean no 
evidence beyond what arises from the mere apprehension of the 
meaning of the symbol a. If we attach no meaning to the 
symbol, it is useless to discuss the value of the probability ; for 
the probability, which belongs to a proposition as an object of 
knowledge, not as a form of words, cannot in such a case exist. 

What exactly does the symbol a stand for in the above ? 
Does it stand for any proposition of which we know no more 
than that it is a proposition ? Or does it stand for a particular 
proposition, which we understand but of which we know no more 
than is involved in understanding it ? In the former case we 


cannot extend our result to a proposition of which we know even 
the meaning ; for we should then know more than that it is a 
proposition ; and in the latter case we cannot say what the 
probability of a is as compared with that of its contradictory, 
until we know what particular proposition it stands for ; for, as 
we have seen, the proposition itself may supply relevant evidence. 
This suggests that a source of much confusion may lie in the 
use of symbols and the notion of variables in probability. In 
the logic of implication, which deals not with probability but 
with truth, what is true of a variable must be equally true of all 
instances of the variable. In Probability, on the other hand, 
we must be on our guard wherever a variable occurs. In Im- 
plication we may conclude that ^ is true of anything of which 
cf> is true. In Probability we may conclude no more than that 
ty is probable of anything of which we only know that < is true of 
it. If x stands for anything of which <f>(x) is true, as soon as 
we substitute in probability any particular value, whose meaning 
we know, for x, the value of the probability may be affected ; 
.for knowledge, which was irrelevant before, may now become 
relevant. Take the following example : Does <>(a) /^r(a) = 
<t>(b)/ty(b) ? That is to say, is the probability of </>'s being true 
of a, given only that -\Jr is true of a, equal to the probability of 
<j>'s being true of 6, given only that ifr is true of b ? If this simply 
means that the probability of an object's satisfying <f> about 
which nothing is known except that it satisfies ^ is equal to 
ditto ditto, the equation is an identity. Eor in this case <(#)/-^(a) 
means the same as <(&)/^(6), i.e. we know nothing about x and y 
except that they satisfy ^, and there is nothing whatever by 
which we can distinguish a from 6. But if a and 6 represent 
specific entities, which we can distinguish, then the equality 
does not necessarily hold. If, for instance, <f>(x) stands for ' x is 
Socrates/ then it is plainly false that $(a)lty(a) = <t>(b)ty(b), where 
a stands for Socrates and b does not. 

19. Bearing this danger in mind, we can now give further 
precision to the enunciation of the Principle of Indifference given 
in 16. Our knowledge of the meaning of a must be taken 
account of so far as it is relevant ; and the Principle is only satis- 
fied if we have corresponding knowledge about the meaning of 6, 
Thus (p(a)/h = <j>(b)/h may be true for one pair of values a, 6, and 
not true for another pair of values a', &'. 


This makes it possible to explain in part the contradiction 
discussed in 4. Even if it were true that the probability of a is 
J, when we know nothing except that a is a proposition, it does 
not follow that the probability of ' This book is red ' is J, when 
we know the meanings of ' book * and ' red/ even if we know no 
more than this. Knowledge arising directly out of acquaintance 
with the meaning of ' red > may be sufficient to enable us to infer 
that e red ' and ' not-red ' are not satisfactory alternatives to 
which to apply the Principle of Indifference. How this may 
come about will be discussed in 20, 21. 

But the contradictions are not yet really solved ; for some 
of the difficulties discussed in 4 can arise even when we know 
no more of a and b than that they are different propositions. In 
fact, although we have now stated more clearly than before how 
the Principle should be enunciated, it is not yet possible to explain 
or to avoid all the contradictions to which it led us in 4 to 7. 
For this purpose we must proceed to a further qualification. 

20. The examples, in which the Principle of Indifference 
broke down, had a great deal in common. We broke up the 
field of possibility, as we may term it, into a number of areas 
by a series of disjunctive judgments. But the alternative areas 
were not ultimate. They were capable of further subdivision 
into other areas similar in kind to the former. The paradoxes 
and contradictions arose, in each case, when the alternatives, 
which the Principle of Indifference treated as equivalent, actually 
contained or might contain a different or an indefinite number of 
more elementary units. 

In the type of cases in which the Principle of Indifference 
seemed to permit the assertion that, in the absence of relevant 
evidence, a proposition is as likely as its contradictory, its con- 
tradictory is not an ultimate and indivisible alternative (in the 
sense to be explained in 21 below), even if the proposition itself 
satisfies this condition. For its contradictory can be disjunct- 
ively resolved into an indefinite number of sets of contraries to 
the proposition. It was out of this that our difficulties first arose. 
6 This book is not red * includes amongst others the alternatives 
* This book is black ' and * This book is blue.' It is not, there- 
fore, an ultimate alternative. 

In the same way the contradiction of 5 arose out of the possi- 
bility of splitting the alternatives c He inhabits the British 


Isles' into the sub-alternatives 'He inhabits Ireland or he 
inhabits Great Britain.' And in the third type of case, to 
which the example of specific volume and density belongs, the 
alternative * v lies in the interval 1 to 2 ' can be broken up into 
the sub-alternatives ' v lies in the interval 1 to 1J or 1|- to 2.' 

21. This, then, seems to point the way to the qualification of 
which we are in search. We must enunciate some formal rule 
which will exclude those cases, in which one of the alternatives 
involved is itself a disjunction of sub-alternatives of the same 
form. For this purpose the following condition is proposed. 

Let the alternatives, the equiprobability of which we seek to 
establish by means of the Principle of Indifference, be $(a-^, 
<(a 2 ) . . . ^far), 1 and let the evidence be h. Then it is a neces- 
sary condition for the application of the principle, that these 
should be, relatively to the evidence, indivisible alternatives of 
the form <(#). We may define a divisible alternative in the 
following manner : 

An alternative <j>(a r ) is divisible if 

(iii.) <jf>(a r /)/A =*: and <(<v)/A=j=0 

The condition that the sub-alternatives must be of the same 
form as the original alternatives, i.e. expressible by means of the 
same prepositional function <f>(x), deserves attention. It might 
be the case that the original alternatives had nothing substantial 
in common ; i.e. <j>(x) s x is the only prepositional function 
common to all of them, the alternatives being %, a 2 , . . ., a r . In, 
these circumstances the condition in question cannot be satisfied. 
For the proposition a r can always be resolved into the disjunction 
a r b+a r 5, where b is any proposition and 5 its contradictory. If, 
on the other hand, the alternatives which we are comparing can 
be expressed in the forms <j>(aj and <(a 2 ), where the function 
<j>(x) is distinct from x, it is not necessarily the case that either 
of these can be resolved into a disjunctive combination of terms 
which can be expressed in their turn in the same form. 

Dispensing with symbolism, we can express these conditions 
as follows : Our knowledge must not enable us to split up the 

1 The more complicated cases in which the prepositional function, of which 
the alternatives are instances, involves more than one variable (see 16), can be 
dealt with in a similar manner mutatis mutandis. 


alternative $(a r ) into a disjunction of two sub-alternatives, (i.) 
which are themselves expressible in the same form <, (ii.) which 
are mutually exclusive, and (iii.) which, on the evidence, are 

In short, the Principle of Indifference is not applicable to a 
pair of alternatives, if we know that either of them is capable of 
being further split up into a pair of possible but incompatible 
alternatives of the same form as the original pair. 

22. This rule commends itself to common sense. If we 
know that the two alternatives are compounded of a different 
number or of an indefinite number of sub-alternatives which are 
in other respects similar, so far as our evidence goes to the 
original alternatives, then this is a relevant fact of which we 
must take account. And as it affects the two alternatives in 
differing and unsymmetrical ways, it breaks down the funda- 
mental condition for the valid application of the Principle of 

Neither this consideration nor that discussed in 18 and 19 
substantially modify the Principle of Indifference as enunciated 
in 16. They have only served to make explicit what was 
always implicit in the Principle, by explaining the manner in 
which our knowledge of the form and meaning of the alternatives 
may be a relevant part of the evidence. The apparent con- 
tradictions arose from paying attention to what we may term 
the extraneous evidence only, to the neglect of such part of the 
evidence as bore upon the form and meaning of the alternatives. 

23. The application of this result to the examples cited in 18 
is not difficult. It excludes the class of cases in which a pro- 
position and its contradictory constitute the alternatives. . For 
if b is the proposition and its contradictory, we cannot find 
a propositional function <f>(x) which will satisfy the necessary 
conditions. It deals also with the type of contradiction which 
arose in considering the probability that an individual taken at 
random was an inhabitant of a given region. If, on the other 
hand, the term * country ' is so defined that one country cannot 
include two countries, then an individual is, relatively to suitable 
hypotheses, as likely to be an inhabitant of one as of another. 
For the function <(#), where <(#) s * the individual is an in- 
habitant of country a?,* satisfies the conditions. And it deals 
with the example of ranges of specific volume and specific density, 


because there is no range which does not contain within itself two 
similar ranges. As there are in this case no definite units by 
which we can define equal ranges, the device, which will be referred 
to in 25 for dealing with geometrical probabilities, is not avail- 

24. It is worth while to add that the qualification of 21 is 
fatal to the practical utility of the Principle of Indifference in 
those cases only in which it is possible to find no ultimate alter- 
natives which satisfy the conditions. For if the original alterna- 
tives each comprise a definite number of indivisible and indifferent 
sub-alternatives, we can compute their probabilities. It is often 
the case, however, that we cannot by any process of finite sub- 
division arrive at indivisible sub-alternatives, or that, if we can, 
they are not on the evidence indifferent. In the examples given 
above, for instance, where <f>(x)=zx, or where # is a part of un- 
specified magnitude in a continuum, there are no indivisible 
sub-alternatives. The first type comprises all cases, amongst 
others, in which we weigh the probabilities of a proposition and 
its contradictory ; and the second includes a great number of 
cases in which physical or geometrical quantities are involved. 

25. We can now return to the numerous paradoxes which 
arise in the study of geometrical probability (see 7, 8). The 
qualification of 21 enables us, I think, to discover the source 
of the confusion. Ouj alternatives in these problems relate to 
certain areas or segments or arcs, and however small the elements 
are which we adopt as our alternatives, they are made up of yet 
smaller elements which would also serve as alternatives. Our 
rule, therefore, is not satisfied, and, as long as we enunciate them 
in this shape, we cannot employ the Principle of Indifference. 
But it is easy in most cases to discover another set of alternatives 
which do satisfy the condition, and which will often' serve our 
purpose equally well. Suppose, for instance, that a point lies 
on a line of length m.L, we may write the alternative ' the interval 
of length I on which the point lies is the xth interval of that 
length as we move along the line from left to right ' ^<f>(x) ; and 
the Principle of Indifference can then be applied safely to the m 
alternatives <(!), <(2) . . . $(m), the number m increasing as the 
length Z of the intervals is diminished. There is no reason why 
Z should not be of any definite length however small. 

If we deal with the problems of geometrical probability in 


this way, we shall avoid the contradictory conclusions, which 
arise from confusing together distinct elementary areas. In the 
problem, for instance, of the chord drawn at random in a circle, 
which is discussed in 7, the chord is regarded, not as a one- 
dimensional line, but as the limit of an area, the shape of which 
is different in each of the variant solutions. In the first solution 
it is the limit of a triangle, the length of the base of which tends 
to zero ; -in the second solution it is the limit of a quadrilateral, 
two of the sides of which are parallel and at a distance apart 
which tends to zero ; and in the third solution the area is defined 
by the limiting position of a central section of undefined shape. 
These distinct hypotheses lead inevitably to different results. If 
we were dealing with a strictly linear chord, the Principle of 
Indifference would yield us no result, as we could not enunciate 
the alternatives in the required form ; and if the chord is an 
elementary area, we must know the shape of the area of which 
it is the limit. So long as we are careful to enunciate the alter- 
natives in a form to which the Principle of Indifference can be 
applied unambiguously, we shall be prevented from confusing 
together distinct problems, and shall be able to reach conclusions 
in geometrical probability which are unambiguously valid. 

The substance of this explanation can be put in a slightly 
different way by saying that it is not a matter of indifference in 
these cases in what manner we proceed to the limit. We must 
assign the probabilities before proceeding to the limit, which 
we can do unambiguously. But if the problem in hand does 
not stop at small finite lengths, areas, or volumes, and we 
have to proceed to the limit, then the final result depends upon 
the shape in which the body approaches the limit. Mathemati- 
cians will recognise an analogy between this case and the deter- 
mination of potential at points within a conductor. Its value 
depends upon the shape of the area which in the limit represents 
the point. 

26. The positive contributions of this chapter to the deter- 
mination of valid judgments of equiprobability are two. In the 
first place we have stated the Principle of Indifference in a more 
accurate form, by displaying its necessary dependence upon 
judgments of relevance and so bringing out the hidden element 
of direct judgment or intuition, which it has always involved. 
It has been shown that the Principle lays down a rule by which 


direct judgments of relevance and irrelevance can lead on to 
judgments of preference and indifference. In the second place, 
some types of consideration, which, are in fact relevant, but which 
are in danger of being overlooked, have been brought into promi- 
nence. By this means it has been possible to avoid the various 
types of doubtful and contradictory conclusions to which the 
Principle seemed to lead, so long as we applied it without due 



1. THE recognition of the fact, that not all probabilities are 
numerical, limits the scope of the Principle of Indifference. It 
has always been agreed that a numerical measure can actually 
be obtained in those cases only in which a reduction to a set of 
exclusive and exhaustive eguiprobable alternatives is practicable. 
Our previous conclusion that numerical measurement is often 
impossible agrees very well, therefore, with the argument of the 
preceding chapter that the rules, in virtue of which we can assert 
equiprobability, are somewhat limited in their field of application. 

But the recognition of this same fact makes it more necessary 
to discuss the principles which will justify comparisons of more 
and less between probabilities, where numerical measurement is 
theoretically, as well as practically, impossible. We must, for 
the reasons given in the preceding chapter, rely in the last resort 
on direct judgment. The object of the following rules and 
principles is to reduce the judgments of preference and relevance, 
which we are compelled to make, to a few relatively simple types. 1 

2. We will enquire first in what circumstances we can expect 
a comparison of more and less to be theoretically possible. I 
am inclined to think that this is a matter about which, rather 
unexpectedly perhaps, we are able to lay down definite rules. 
We are able, I think, always to compare a pair of probabilities 
which are 

(i.) of the type ab/h and a/h, 
or (ii.) of the type aflih^ and a/h, 

provided the additional evidence h^ contains only one inde- 
pendent piece of relevant information. 

1 Parts of Chap. XV. are closely connected with the topics of the follow- 
ing paragraphs, and the discussion which is commenced here is concluded there. 

65 F 


(i.) The propositions of Part II. will enable us to prove that 
ab/h < a/h unless b/ah = 1 ; 

that is to say, the probability of our conclusion is diminished by 
the addition to it of something, which on the hypothesis of our 
argument cannot be inferred from it. This proposition will be 
self-evident to the reader. The rule, that the probability of two 
propositions jointly is, in general, less than that of either of them 
separately, includes the rule that the attribution of a more 
specialised concept is less probable than the attribution of a less 
specialised concept. 

(ii.) This condition requires a little more explanation. It 
states that the probability a\Hh l is always greater than, equal to, 
or less than the probability a/h, if ^ contains no pair of comple- 
mentary and independent parts * both relevant to a/h. If \ 
is favourable, a/hh^ > a/h. Similarly, if h 2 is favourable to a/hh^ 
a/hh]Ji 2 > a/hh^ The reverse holds if \ and 7^ are unfavourable. 
Thus we can compare a/hh' and a/h, in every case in which the 
relevant independent parts of the additional evidence In! are 
either all favourable, or all unfavourable. In cases in which our 
additional evidence is equivocal, part taken by itself being favour- 
able and part unfavourable, comparison is not necessarily possible. 
In ordinary language we may assert that, according to our rule, 
the addition to our evidence of a single fact always has a definite 
bearing on our conclusion. It either leaves its probability un- 
affected and is irrelevant, or it has a definitely favourable or 
unfavourable bearing, being favourably or unfavourably relevant. 
It cannot affect the conclusion in an indefinite way, which allows 
no comparison between the two probabilities. But if the addition 
of one fact is favourable, and the addition of a second is unfavour- 
able, it is not necessarily possible to compare the probability of 
our original argument with its probability when it has been 
modified by the addition of both the new facts. 

Other comparisons are possible by a combination of these 
two principles with the Principle of Indifference. We may 
find, for instance, that a/hh^a/h, that a/h = b/h, that b/h>b/hh 2 , 
and that, therefore, a/M 1 >6/M 2 . We have thus obtained a 
comparison between a pair of probabilities, which are not 
of the types discussed above, but without the introduction 

1 See Chap. IV. 14 for the meaning of these terms. 


of any fresh, principle. We may denote comparisons of this 
type by (iii.)- 

3. Whether any comparisons are possible which do not fall 
within any of the categories (i.), (ii.). or (iii.), I do not feel certain. 
We undoubtedly make a number of direct comparisons which 
do not seem to be covered by them. We judge it more probable, 
for instance, that Caesar invaded Britain than that Eomulus 
founded Eome. But even in such cases as this, where a reduction 
into the regular form is not obvious, it might prove possible if 
we could clearly analyse the real grounds of our judgment. We 
might argue in this instance that, whereas Romulus's founding of 
Rome rests solely on tradition, we have in addition evidence of 
another kind for Caesar's invasion of Britain, and that, in so 
far as our belief in Caesar's invasion rests on tradition, we have 
reasons of a precisely similar kind as for our belief in Romulus 
without the additional doubt involved in the maintenance of a 
tradition between the times of Romulus and Caesar. By some 
such analysis as this our judgment of comparison might be 
brought within the above categories. 

The process of reaching a judgment of comparison in this way 
may be called * schematisation/ x We take initially an ideal 
scheme which falls within the categories of comparison. Let 
us represent ' the historical tradition x has been handed down 
from a date many years previous to the time of Caesar 9 by 
^ t (a;); 'the historical tradition a? has been handed down from 
the time of Caesar' by fafa) ; c the historical tradition x has 
extra-traditional support ' by -^3(0?) ; and the two traditions, 
the Romulus tradition and the Caesar tradition respectively, 
by a and b. Then if our relevant evidence h were of the form 
^ 1 (a)T/r 2 (6)'^r3(6), it is easily seen that the comparison a/h<b/h 
could be justified on the lines laid down above. 2 A further judg- 
ment, that our actual evidence presented no relevant divergence 
from this schematic form, would then establish the practical 
conclusion. As I am not aware of any plausible judgment of 
comparison which we make in common practice, but which is 
clearly incapable of reduction to some schematic form, and as 
I see no logical basis for such a comparison, I feel justified in 

1 This phrase is used by Von BLries, op. cit. p. 179, in a somewhat similar 

8 For *I 
a/ft (a) = a/h ; and 


doubting the possibility of comparing the probabilities of argu- 
ments dissimilar in form and incapable of schematic reduction. 
But the point must remain very doubtful until this part of the 
subject has received a more prolonged consideration. 

4. Category (ii.) is very wide, and evidently covers a great 
variety of cases. If we are to establish general principles of argu- 
ment and so avoid excessive dependence on direct individual 
judgments of relevance, we must discover some new and more 
particular principles included within it. Two of these those 
of Analogy and of Induction are excessively important, and 
will be the subject of Part III. of this book. In addition to these 
a few criteria will be examined and established in Chapter XIV., 
4 and 8 (49.1). We must be content here (pending the 
symbolic developments of Part II.) with the two observations 
following : 

(1) The addition of new 1 evidence ^ to a doubtful 2 argument 
a/h is favourably relevant, if either of the following conditions 
is fulfilled : (a) if 0/^=0 ; (b) if a/M x = l. Divested of sym- 
bolism, this merely amounts to a statement that a piece of 
evidence is favourable if, in conjunction with the previous 
evidence, it is either a necessary or a sufficient condition for the 
truth of our conclusion. 

(2) It might plausibly be supposed that evidence would be 
favourable to our conclusion which is favourable to favourable 
evidence i.e. that, if \ is favourable to x/Ji and x is favourable to 
a/Tiy Th is favourable to a/k. Whilst, however, this argument 
is frequently employed under conditions, which, if explicitly 
stated, would justify it, there are also conditions in which this is 
not so, so that it is not necessarily valid. For the very deceptive 
fallacy involved in the above supposition, Mr. Johnson, has 
suggested to me the name of the Fallacy of the Middle Term. The 
general question If \ is favourable to xfh and x is favourable to 
a/Ji, in what conditions is ^ favourable to a/h ? will be examined 
in Chapter XIV. 4 and 8 (49.1). In the meantime, the intui- 
tion of the reader towards the fallacy may be assisted by the 
following observations, which are due to Mr. Johnson : 

Let x. x' y x" . . . be exclusive and exhaustive alternatives 
under datum h. Let \ and a be concordant in regard to each of 

1 Aj is new evidence so long as "h^fh 4= 1. 
2 The argument is doubtful so long as a/h is neither certain nor impossible. 


these alternatives : i.e. any hypothesis which is strengthened by 
^ will strengthen a, and any hypothesis which is weakened by 
h^ will weaken a. It is obvious that, if A x strengthens some of 
the hypotheses x, #', %" . . ., it will weaken otJiers. This fact 
helps us to see why we cannot consider the concordance of h^ 
and a in regard to one single alternative, but must be able to 
assert their concordance with regard to every one of the exclusive 
and exhaustive alternatives, including the particular one taken. 
But a further condition js needed, which (as we shall show) is 
obviously satisfied in two typical problems at least. This further 
condition is that, for each hypothesis x, x f , x" . . ., it shall hold 
that, were this hypothesis known to be true, the knowledge of 
7^ would not weaken the probability of a. 

These two conditions are sufficient to ensure that \ shall 
strengthen a (independently of knowledge of x 3 #', a?" . . .) ; 
and, in a sense, they appear to be necessary ; for, unless they are 
satisfied, the dependence of ^ upon a would be (so to speak) 
accidental as regards the ' middle terms,' (x, x', x" . . .). 

The necessity for reference to all the alternatives x, x', x" . . . 
is analogous to the requirement of distribution of the middle 
term in ordinary syllogism. Thus, from premises " All P is x, 
all S is x," the conclusion that " S's are P " does not formally 
follow ; but given " all P is # and all S is a?' " it does follow that 
" no S are P ", where x r is any contrary to x. The two conditions 
taken together would be analogous to the argument : all # S is 
P ; all x' S is P ; all x" S is P ; . . . therefore all S is P. 

First Typical Problem. An urn contains an unknown pro- 
portion of differently coloured balls. A ball is drawn and replaced. 
Then x, x', x" . . . stand for the various possible proportions. 
Let A! mean " a white ball has been drawn " ; and let a mean 
" a white ball will be again drawn." Then any hypothesis which 
is strengthened by 7^ will strengthen a ; and any hypothesis 
which is weakened by h will weaken a. Moreover, were any 
one of these hypotheses known to be true, the knowledge of h 
would not weaken the probability of a. Hence, in the absence 
of definite knowledge as regards x, x', x" . . ., the knowledge 
of \ would strengthen the probability of a. 

Second Typical Problem. Let a certain event have taken 
place ; which may have been x 9 x', x" or ... Let \ mean that 
A reports so and so ; and let a mean that B reports similarly or 


identically. The pkrase similarly merely indicates that any 
hypothesis as to the actual fact, which would be strengthened by 
A's report, would be strengthened by B's report. Of course, 
even if the reports were verbally identical., A's evidence would not 
necessarily strengthen the hypothesis in an equal degree with 
B's ; because A and B may be unequally expert or intelligent. 
Now, in such cases, we may further affirm (in general), that, were 
the actual nature of the event known, the knowledge of A's report 
on it would not weaken (though it also need not strengthen) the 
probability that B would give a similar report. Hence, in the 
absence of such knowledge, the knowledge of ^ would strengthen 
the probability of a. 

5. Before leaving this part of the argument we must emphasise 
the part played by direct judgment in the theory here presented. 
The rules for the determination of equality and inequality between 
probabilities all depend upon it at some point. This seems to 
me quite unavoidable. But I do not feel that we should regard 
it as a weakness. For we have seen that most, and perhaps all, 
cases can be determined by the application of general principles 
to one simple type of direct judgment. No more is asked of the 
intuitive power applied to particular cases than to determine 
whether a new piece of evidence tells, on the whole, for or against 
a given conclusion. The application of the rules involves no 
wider assumptions than those of other branches of logic. 

While it is important, in establishing a control of direct 
judgment by general principles, not to conceal its presence, yet 
the fact that we ultimately depend upon an intuition need not 
lead us to suppose that our conclusions have, therefore, no basis 
in reason, or that they are as subjective in validity as they are 
in origin. It is reasonable to maintain with the logicians of the 
Port Royal that we may draw a conclusion which is truly probable 
by paying attention to all the circumstances which accompany 
the case, and we must admit with as little concern as possible 
Hume's taunt that " when we give the preference to one set of 
arguments above another, we do nothing but decide from our 
feeling concerning the superiority of their influence." 



1. THE question to be raised in this chapter is somewhat novel ; 
after much consideration I remain uncertain as to how much 
importance to attach to it. The magnitude of the probability 
of an argument, in the sense discussed in Chapter III., depends 
upon a balance between what may be termed the favourable and 
the unfavourable evidence ; a new piece of evidence which leaves 
this balance unchanged, also leaves the probability of the argu- 
ment unchanged. But it seems that there may he another 
respect in which some kind of quantitative comparison between 
arguments is possible. This comparison turns upon a balance, 
not between the favourable and the unfavourable evidence, but 
between the absolute amounts of relevant knowledge and of 
relevant ignorance respectively. 

As the relevant evidence at our disposal increases, the magni- 
tude of the probability of the argument may either decrease or 
increase, according as the new knowledge strengthens the un- 
favourable or the favourable evidence ; but something seems to 
have increased in either case, we have a more substantial basis 
upon which to rest our conclusion. I express this by saying that 
an accession of new evidence increases the weight of an argu- 
ment. New evidence will sometimes decrease the probability of 
an argument, but it will always increase its c weight.' 

2. The measurement of evidential weight presents similar 
difficulties to those with which we met in the measurement of 
probability. Only in a restricted class of cases can we compare 
the weights of two arguments in respect of more and less. But 
this must always be possible where the conclusion of the two 
fl.rgiirnp.-n-f-.fl is the same, and the relevant evidence in the one in- 
cludes and exceeds the evidence in the other. If the new evidence 



is ' irrelevant/ in the more precise of the two senses defined in 14 
of Chapter IV., the weight is left unchanged. If any part of the 
new evidence is relevant, then the value is increased. 

The reason for our stricter definition of * relevance * is now 
apparent. If we are to be able to treat ' weight ' and ' relevance ' 
as correlative terms, we must regard evidence as relevant, part 
of which is favourable and part unfavourable, even if, taken as 
a whole, it leaves the probability unchanged. With this defini- 
tion, to say that a new piece of evidence is relevant ' is the same 
thing as to say that it increases the ' weight ' of the argument. 

A proposition cannot be the subject of an argument, unless 
we at least attach some meaning to it, and this meaning, even if 
it only relates to the form of the proposition, may be relevant 
in some arguments relating to it. But there may be no other 
relevant evidence ; and it is sometimes convenient to term the 
probability of such an argument an d priori probability. In 
this case the weight of the argument is at its lowest. Start- 
ing, therefore, with minimum weight, corresponding to d priori 
probability, the evidential weight of an argument rises, though 
its probability may either rise or fall, with every accession of 
relevant evidence. 

3. Where the conclusions of two arguments are different, or 
where the evidence for the one does not overlap the evidence 
for the other, it will often be impossible to compare their weights, 
just as it may be impossible to compare their probabilities. Some 
rules of comparison, however, exist, and there seems to be a close, 
though not a complete, correspondence * between the conditions 
under which pairs of arguments are comparable in respect of 
probability and of weight respectively. We found that there were 
three principal types in which comparison of probability was 
possible, other comparisons being based on a combination of 
these : 

(i.) Those based on the Principle of Indifference, subject 
to certain conditions, and of the form 
where A 1 and h 2 are irrelevant to the arguments. 

(ii.) a/hh^a/hy where A X is a single unit of information, 
containing no independent parts which are relevant. 

(iii.) abjh^ajh. 

Let us represent the evidential weight of the argument, 
whose probability is a/h, by V(a/A). Then, corresponding to 


the above, we find that the following comparisons of weight are 
possible : 

(i.) V(<f>a/-^a\) = V(^*/^r&.A 2 ), where \ and A 2 are irrelevant 
in the strict sense. Arguments, that is to say, to which the 
Principle of Indifference is applicable, have equal evidential 

(ii.) V(a/AA 1 )>V(a/7i), unless \ is irrelevant, in which case 
V(a/7&7t 1 )==V(a/7fc). The restriction on the composition of A 15 
which is necessary in the case of comparisons of magnitude, is 
not necessary in the case of weight. 

There is, however, no rule for comparisons of weight corre- 
sponding to (iii.) above. It might be thought that V(a6/) < V(a/A), 
on the ground that the more complicated an argument is, relative 
to given premisses, the less is its evidential weight. But this 
is invalid. The argument abfh is further off proof than was the 
argument a/h ; but it is nearer disproof. For example, if ab/Ji0 
and a/A>0, then V(db/h) > V(a/A). In fact it would seem to 
be the case that the weight of the argument a/A is always 
equal to that of a/A, where a is the contradictory of a ; i.e., 
V(a/A)=sV(a/A). For an argument is always as near proving or 
disproving a proposition, as it is to disproving or proving its 

4. It may be pointed out that if a/h = 6/A, it does not neces- 
sarily follow that V(a/A)=V(6/A). It has been asserted already 
that if the first equality follows directly from a single application of 
the Principle of Indifference, the second equality also holds. But 
the first equality can exist in other cases also. If, for instance, 
a and 6 are members respectively of different sets of three equally 
probable exclusive and exhaustive alternatives, then a/A = 6/A; but 
these arguments may have very different weights. If, however, 
a and 6 can each, relatively to A, be inferred from the other, i.e. if 
a/6A = 1 and bfah = 1, then V(a/A) = V(6/A). For in proving or dis- 
proving one, we are necessarily proving or disproving the other. 

Further principles could, no doubt, be arrived at. The above 
can be combined to reach results in cases upon which unaided 
common-sense might feel itself unable to pronounce with con- 
fidence. Suppose, for instance, that we have three exclusive 
and exhaustive alternatives, a, 6, and c, and that a/A = fc/A 
in virtue of the Principle of Indifference, then we have 
V(a/A) = V(6/A) and V(a/A) = V(a/A), so that V(6/A) - V(a/A). It is 


also true, since a/(6 + c)^ = l and (6 + c)/a& = l, that V(d/h) = 
V((6 + c)/A). Hence V(6/A) = V((6 + c)/A). 

5. The preceding paragraphs will have made it clear that the 
weighing of the amount of evidence is quite a separate process 
from the balancing of the evidence for and against. In so far, 
however, as the question of weight has been discussed at all, 
attempts have been made, as a rule, to explain the former in 
terms of the latter. If x/hj^ ^ and z/A^f, it has sometimes 
been supposed that it is more probable that xjhji 2 really is |- than 
that x/h^ really is f . According to this view, an increase in the 
amount of evidence strengthens the probability of the proba- 
bility, or, as De Morgan would say, the presumption of the 
probability. A little reflection will show that such a theory is 
untenable. For the probability of x on hypothesis \ is inde- 
pendent of whether as a matter of fact a? is or is not true, and if 
we find out subsequently that x is true, this does not make it 
false to say that on hypothesis ^ the probability of x is f , Simi- 
larly the fact that a/h-Ji^ is f does not impugn the conclusion that 
xfy is J, and unless we have made a mistake in our judgment or 
our calculation on the evidence, the two probabilities are and f 

6. A second method, by which it might be thought, perhaps, 
that the question of weight has been treated, is the method of 
probable error. But while probable error is sometimes connected 
with weight, it is primarily concerned with quite a different ques- 
tion. 'Probable error,' it should be explained, is the name 
given, rather inconveniently perhaps, to an expression which 
arises when we consider the probability that a given quantity is 
measured by one of a number of different magnitudes. Our 
data may tell us that one of these magnitudes is the most probable 
measure of the quantity ; but in some cases it will also tell 
us how probable each of the other possible magnitudes of the 
quantity is. In such cases we can determine the probability 
that the quantity will have a magnitude which does not differ 
from the most probable by more than a specified amount. The 
amount, which the difference between the actual value of the 
quantity and its most probable value is as likely as not to exceed, 
is the ' probable error.' In many practical questions the exist- 
ence of a small probable error is of the greatest importance, 
if our conclusions are to prove valuable. The probability that 


the quantity has any particular magnitude may be very small ; 
but this may matter very little, if there- is a high probability 
that it lies within a certain range. 

Now it is obvious that the determination of probable error 
is intrinsically a different problem from the determination of 
weight. The method of probable error is simply a summation of 
a number of alternative and exclusive probabilities. If we say 
that the most probable magnitude is x and the probable error y, 
this is a way, convenient for many purposes, of summing up a 
number of probable conclusions regarding a variety of magni- 
tudes other than x which, on the evidence, the quantity may 
possess. The connection between probable error and weight, such 
as it is, is due to the fact that in scientific problems a large 
probable error is not uncommonly due to a great lack of evidence, 
and that as the available evidence increases there is a tendency 
for the probable error to dimmish. In these cases the probable 
error may conceivably be a good practical measure of the weight. 

It is necessary, however, in a theoretical discussion, to point 
out that the connection is casual, and only exists in a limited 
class of cases. This is easily shown by an example. We may 
have data on which the probability of x = 5 is , of x 6 is J, 
of x = 7 is i, of x = 8 is , and of x = 9 is -fa. Additional evidence 
might show that x must either be 5 or 8 or 9, the probabilities of 
each of these conclusions being T V, xV> rV- The evidential weight 
of the latter argument is greater than that of the former, but the 
probable error, so far from being diminished, has been increased. 
There is, in fact, no reason whatever for supposing that the 
probable error must necessarily diminish,, as the weight of the 
argument is increased. 

The typical case, in which there may be a practical connection 
between weight and probable error, may be illustrated by the 
two cases following of balls drawn from an uin. In each case we 
require the probability of drawing a white ball ; in the first case 
we know that the urn contains black and white in equal propor- 
tions ; in the second case the proportion of each colour is unknown, 
and each ball is as likely to be black as white. It is evident that 
in either case the probability of drawing a white ball is J, but 
that the weight of the argument in favour of this conclusion is 
greater in the first case. When we consider the most probable 
proportion in which balls will be drawn in the long run, if after 


each withdrawal they are replaced, the question of probable 
error enters in, and we find that the greater evidential weight of 
the argument on the first hypothesis is accompanied by the 
smaller probable error. 

This conventionalised example is typical of many scientific 
problems. The more we know about any phenomenon, the less 
likely, as a rule, is our opinion to be modified by each additional 
item of experience. In such problems, therefore, an argument 
of high weight concerning some phenomenon is likely to be accom- 
panied by a low probable error, when the character of a series 
of similar phenomena is under consideration. 

7. Weight cannot, then, be explained in terms of probability. 
An argument of high weight is not ' more likely to be right ' than 
one of low weight ; for the probabilities of these arguments only 
state relations between premiss and conclusion, and these re- 
lations are stated with equal accuracy in either case. Nor is an 
argument of high weight one in which the probable error is small ; 
for a small probable error only means that magnitudes in the 
neighbourhood of the most probable magnitude have a relatively 
high probability, and an increase of evidence does not necessarily 
involve an increase in these probabilities. 

The conclusion, that the ' weight ' and the ' probability * of an 
argument are independent properties, may possibly introduce a 
difficulty into the discussion of the application of probability 
to practice. 1 For in deciding on a course of action, it seems 
plausible to suppose that we ought to take account of the weight 
as well as the probability of different expectations. But it is 
difficult to think of any clear example of this, and I do not 
feel sure that the theory of e evidential weight * has much 
practical significance. 

Bernoulli's second maxim, that we must take into account all 
the information we have, amounts to an injunction that we should 
be guided by the probability of that argument, amongst those of 
which we know the premisses, of which the evidential weight is 
the greatest. But should not this be re-enforced by a further 
maxim, that we ought to make the weight of our arguments as 
great as possible by getting all the information we can ? a It is 

1 See also Chapter XXVI. 7. 

2 Of. Locke, Essay concerning Human Understanding, book ii. chap. xxi. 67 : 
" He that judges -mthout informing himself to the utmost that ho is capable, 
cannot acquit himself of judging amiss." 


difficult to see, however, to what point the strengthening of an 
argument's weight by increasing the evidence ought to be pushed. 
We may argue that, when our knowledge is slight but capable of 
increase, the course of action, which will, relative to such know- 
ledge, probably produce the greatest amount of good, will often 
consist in the acquisition of more knowledge. But there clearly 
comes a point when it is no longer worth while to spend trouble, 
before acting, in the acquisition of further information, and there 
is no evident principle by which to determine how far we ought 
to carry our maxim of strengthening the weight of our argument. 
A little reflection will probably convince the reader that this is 
a very confusing problem. 

8. The fundamental distinction of this chapter may be briefly 
repeated. One argument has more weight than another if it is 
based upon a greater amount of relevant evidence ; but it is not 
always, or even generally, possible to say of two sets of proposi- 
tions that one set embodies more evidence than the other. It has 
a greater probability than another if the balance in its favour, 
of what evidence there is, is greater than the balance in favour 
of the argument with which we compare it ; but it is not always, 
or even generally, possible to say that the balance in the one case 
is greater than the balance in the other. The weight, to speak 
metaphorically, measures the sum of the favourable and unfavour- 
able evidence, the probability measures the difference,. 

9. The phenomenon of c weight ' can be described from the 
point of view of other theories of probability than that which is 
adopted here. If we follow certain German logicians in regarding 
probability as being based on the disjunctive judgment, we may 
say that the weight is increased when the number of alternatives 
is reduced, although the ratio of the number of favourable to 
the number of unfavourable alternatives may not have been 
disturbed ; or, to adopt the phraseology of another German 
school, we may say that the weight of the probability is increased, 
as the field of possibility is contracted. 

The same distinction may be explained in the language of the 
frequency theory. 1 We should then say that the weight is in- 
creased if we are able to employ as the class of reference a class 
which is contained in the original class of reference. 

10. The subject of this chapter has not usually been discussed 

1 See Chap. VUL 


by writers on probability, and I know of only two by whom the 
question has been explicitly raised : * Meinong, who threw out a 
suggestion at the conclusion of his review of Von Kries' " Princi- 
pien," published in the Gottingische gelehrte Anzeigen for 1890 
(see especially pp. 70-74), and A. Nitsche, who took up Meinong's 
suggestion in an article in the VierteljdhrsscJvrift fur wissenschaft- 
liche Philosophic, 1892, vol. xvi. pp. 20-35, entitled "Die Dimen- 
sionen der Wahrscheiolichkeit und die Evidenz der Ungewissheit." 
Meinong, who does not develop the point in any detail, dis- 
tinguishes probability and weight as e Intensitat ' and c Qualitat/ 
and is inclined to regard them as two independent dimensions in 
which the judgment is free to move they are the two dimensions 
of the * Urteils-Continuum.' Nitsche regards the weight as being 
the measure of the reliability (Sicherheit) of the probability, and 
holds that the probability continually approximates to its true 
magnitude (reale Geltung) as the weight increases. His treatment 
is too brief for it to be possible to understand very clearly what 
he means, but his view seems to resemble the theory already 
discussed that an argument of high weight is ' more likely to be 
right J than one of low weight. 

1 There are also some remarks by Czuber (Wahrsckeinh'r/tkeitsrechrmng, 
vol. i. p. 202) on the ErTcenntnisswert of probabilities obtained by different 
methods, which may have been intended to have some bearing on it. 



1. THE characteristic features of our Philosophy of Probability 
must be determined by the solutions which, we offer to the 
problems attacked in Chapters III. and IV. Whilst a great part 
of the logical calculus, which will be developed in Part II., would 
be applicable with slight modification to several distinct theories 
of the subject, the ultimate problems of establishing the premisses 
of the calculus bring into the light every fundamental difference 
of opinion. 

These problems are often, for this reason perhaps, left on one 
side by writers whose interest chiefly lies in the more formal parts 
of the subject. But Probability is not yet on so sound a basis 
that the formal or mathematical side of it can be safely developed 
in isolation, and some attempts have naturally been made to 
solve the problem which Bishop Butler sets to the logician in the 
concluding words of the brief discussion on probability with 
which he prefaces the Analogy?- 

In this chapter, therefore, we will review in their historical 
order the answers of Philosophy to the questions, how we know 
relations of probability, what ground we have for our judgments, 
and by what method we can advance our knowledge. 

2. The natural man is disposed to the opinion that probability 
is essentially connected with the inductions of experience and, 
if he is a little more sophisticated, with the Laws of Causation 

1 " It is not my design to inquire further into the nature, the foundation and 
measure of probability ; or whence it .proceeds that likeness should beget that 
presumption, opinion and full conviction, which the human mind is formed 
to receive from it, and which it does necessarily produce in every one ; or to 
guard against the errors to which reasoning from analogy is liable. This 
belongs to the subject of logic, and is a part of that subject which has not yet 
been thoroughly considered." 



and of the Uniformity of Nature. As Aristotle says, u the 
probable is that which usually happens." Events do not always 
occur in accordance with the expectations of experience ; but 
the laws of experience afford us a good ground for supposing 
that they usually will. The occasional disappointment of these 
expectations prevents our predictions from being more than 
probable ; but the ground of their probability must be sought in 
this experience, and in this experience only. 

This is, in substance, the argument of the authors of the Port 
Royal Logic (1662), who were the first to deal with the logic 
of probability in the modern manner : " In order for me to 
judge of the truth of an event, and to be determined to believe 
it or not believe it, it is not necessary to consider it abstractly, 
and in itself, as we should consider a proposition in geometry ; 
but it is necessary to pay attention to all the circumstances 
which accompany it, internal as well as external. I call internal 
circumstances those which belong to the fact itself, and external 
those which belong to the persons by whose testimony we are led 
to believe it. This being done, if all the circumstances are 
such that it never or rarely happens that the like circumstances 
are the concomitants of falsehood, our mind is led, naturally, 
to believe that it is true." 1 Locke follows the Port Royal 
Logicians very closely : " Probability is likeliness to be true. . . . 
The grounds of it are, in short, these two following. First, the 
conformity of anything with our own knowledge, observation, 
and experience. Secondly, the testimony of others, vouching 
their observation and experience " ; 2 and essentially the same 
opinion is maintained by Bishop Butler : " When we determine 
a thing to be probably true, suppose that an event has or will 
come to pass, it is from the mind's remarking in it a likeness to 
some other event, which we have observed has come to pass. 
And this observation forms, in numberless instances, a pre- 
sumption, opinion, or full conviction that such event has or will 
come to pass." 8 

Against this view of the subject the criticisms of Hume were 
directed : " The idea of cause and effect is derived from experi- 
ence, which informs us, that such particular objects, in all past 

1 Eng. Trans., p. 353. 

8 An Essay concerning Human Understanding, book iv. " Of Knowledge and 

8 Introduction to the Analogy. 


instances, have been constantly conjoined with, each other. 
According to this account of things . . . probability is founded 
on the presumption of a resemblance betwixt those objects, of 
which we have had experience, and those, of which we have had 
none ; and therefore 'tis impossible this presumption can arise 
from probability." x "When we are accustomed to see two impres- 
sions conjoined together, the appearance or idea of the one im- 
mediately carries us to the idea of the other. . . . Thus all prob- 
able reasoning is nothing but a species of sensation. 'Tis not 
solely in poetry and music > we must follow our taste and senti- 
ment, but likewise in philosophy. When I am convinced of any 
principle, 'tis only an idea, which strikes more strongly upon me. 
When I give the preference to one set of arguments above another, 
I do nothing but decide from my feeling concerning the superi- 
ority of their influence." 2 Hume, in fact, points out that, while 
it is true that past experience gives rise to a psychological anticipa- 
tion of some events rather than of others, no ground has been 
given for the validity of this superior anticipation. 

3. But in the meantime the subject had fallen into the hands 
of the mathematicians, and an entirely new method of approach 
was in course of development. It had become obvious that 
many of the judgments of probability which we in fact make 
do not depend upon past experience in a way which satisfies the 
canons laid down by the Port Royal Logicians or by Locke. In 
particular, alternatives are judged equally probable, without 
there being necessarily any actual experience of their approxi- 
mately equal frequency of occurrence in the past. And, apart 
from this, it is evident that judgments based on a somewhat 
indefinite experience of the past do not easily lend them- 
selves to precise numerical appraisement. Accordingly James 
Bernoulli, 3 the real founder of the classical school of mathematical 
probability 3 while not repudiating the old test of experience, had 
based many of his conclusions on a quite different criterion the 
rule which I have named the Principle of Indifference. The 
traditional method of the mathematical school essentially 
depends upon reducing all the possible conclusions to a number 
of * equi-probable cases.' And, according to the Principle of 

1 Treatise of Human Nature, p. 391 (Green's edition). 
* Op. tit. p. 403. 

3 See especially Ars Oowjectandi, p. 224. Of. Laplaoe, Thtorie aTialytique, 
p. 178. 


Indifference, ' cases * are held to be equi-probable when there 
is no reason for preferring any one to any other, when there is 
nothing, as with Buridan's ass, to determine the mind in any one 
of the several possible directions. To take Czuber's example 
of dice, 1 this principle permits us to assume that each face is 
equally likely to fall, if there is no reason to suppose any particular 
irregularity, and it does not require that we should know that the 
construction is regular, or that each face has, as a matter of fact, 
fallen equally often in the past. 

On this Principle, extended by Bernoulli beyond those 
problems of gaming in which by its tacit assumption Pascal 
and Huyghens had worked out a few simple exercises, the whole 
fabric of mathematical probability was soon allowed to rest. 
The older criterion of experience, never repudiated, was soon 
subsumed under the new doctrine. First, in virtue of Bernoulli's 
famous Law of Great Numbers, the fractions representing the 
probabilities of events were thought to represent also the actual 
proportion of their occurrences, so that experience, if it were 
considerable, could be translated into the cyphers of arithmetic. 
And next, by the aid of the Principle of Indifference, Laplace 
established his Law of Succession by which the influence of any 
experience, however limited, could be numerically measured, and 
which purported to prove that, if B has been seen to accompany 
A twice, it is two to one that B will again accompany A on A's 
next appearance. No other formula in the alchemy of logic 
has exerted more astonishing powers. For it has established 
the existence of God from the premiss of total ignorance ; and it 
has measured with numerical precision the probability that the 
sun will rise to-morrow. 

Yet the new principles did not win acceptance without 
opposition. D'Alembert, 2 Hume, and Ancillon 3 stand out as 
the sceptical critics of probability, against the credulity of 

1 Wahrscheirilichkeitsrechnung, p. 9. 

* D'Alembert's scepticism was directed towards the current mathematical 
theory only, and was not, like Hume's, fundamental and far-reaching. His 
opposition to the received opinions was, perhaps, more splendid than dis- 

3 Ancillon's communication to the Berlin Academy in 1794, entitled JDoutes 
mr les bases du cdlcul des probability, is not as well known as it deserves to 
he. He writes as a follower of Hume, but adds much that is original and 
interesting. An historian, who also wrote on a variety of philosophical subjects, 
Ancillon. was, at one time, the Prussian Minister of Foreign Affairs. 


eighteenth-century philosophers who were ready to swallow 
without too many questions the conclusions of a science which 
claimed and seemed to bring an entire new field within the 
dominion of Reason. 1 

The first effective criticism came from Hume, who was also 
the first to distinguish the method of Locke and the philosophers 
from the method of Bernoulli and the mathematicians. " Prob- 
ability/' he says, " or reasoning from conjecture, may be divided 
into two kinds, viz. that which is founded on chance and that which 
arises from causes." 2 By these two kinds he evidently means the 
mathematical method of counting the equal chances based on 
Indifference, and the inductive method based on the experience 
of uniformity. He argues that e chance ' alone can be the 
foundation of nothing, and " that there must always be a mixture 
of causes among the chances, in order to be the foundation of 
any reasoning." 3 His previous argument against probabilities, 
which were based on an assumption of cause, is thus extended 
to the mathematical method also. 

But the great prestige of Laplace and the ' verifications ' 
of his principles which his more famous results were supposed 
to supply had, by the beginning of the nineteenth century, 
established the science on the Principle of Indifference in an 
almost unquestioned position. It may be noted, however, that 
De Morgan, the principal student of the subject in England, 
seems to have regarded the method of actual experiment and 
the method of counting cases, which were equally probable 
on grounds of Indifference, as alternative methods of equal 

4. The reaction against the traditional teaching during the 
past hundred years has not possessed sufficient force to displace 

1 French philosophy of the latter half of the eighteenth century was pro- 
foundly affected by the supposed conquests of the Calculus of Probability in 
all fields of thought. Nothing seemed beyond its powers of prediction, and 
it almost succeeded in men's minds to the place previously occupied by 
Revelation. It was under these influences that Condorcet evolved his doctrine 
of the perfectibility of the human race. The continuity and oneness of 
modern European thought may be illustrated, if such things amuse the 
reader, by the reflection that Condorcet derived from Bernoulli, that Godwin 
was inspired by Condorcet, that Malthus was stimulated by Godwin's folly 
into stating his famous doctrine, and that from the reading of Malthus 
on Population Darwin received his earliest impulse. 

2 Treatise of Human Nature, p. 424 (Green's edition). 
' 3 Op. cit. p. 425. 


the established doctrine, and the Principle of Indifference is 
still very widely accepted in an unqualified form. Criticism 
has proceeded along two distinct lines ; the one, originated by 
Leslie Ellis, and developed by Dr. Venn, Professor Edgeworth, 
and Professor Karl Pearson, has been almost entirely confined 
in its influence to England ; the other, of which the beginnings 
are to be seen in Boole's Laws of Thought, has been developed 
in Germany, where its ablest exponent has been Von Kries. 
France has remained uninfluenced by either, and faithful, on 
the whole, to the tradition of Laplace. Even Henri PoincarS, 
who had his doubts, and described the Principle of Indifference 
as "very vague and very elastic," regarded it as our only 
guide in the choice of that convention, " which has always 
something arbitrary about it," but upon which calculation in 
probability invariably rests. 1 

5. Before following up in detail these two lines of develop- 
ment, I will summarise again the earlier doctrine with which the 
leaders of the new schools found themselves confronted. 

The earlier philosophers had in mind in dealing with prob- 
ability the application to the future of the inductions of experience, 
to the almost complete exclusion of other problems. For the 
data of probability, therefore, they looked only to their own 
experience and to the recorded experiences of others ; their 
principal refinement was to distinguish these two grounds, and 
they did not attempt to make a numerical estimate of the chances. 
The mathematicians, on the other hand, setting out from the 
simple problems presented by dice and playing cards, and 

1 PoincarS's opinions on Probability are to be found in his Calcul des Prob- 
abilites and in his Science et Hypothese. Neither of these books appears 
to me to be in all respects a considered work, but his view is sufficiently novel 
to be worth a reference. Briefly, he shows that the current mathematical 
definition is circular, and argues from this that the choice of the particular 
probabilities, which we are to regard as initially equal before the application of 
our mathematics, is entirely a matter of ' convention.' Much epigram is, 
therefore, expended in pointing out that the study of probability is no more 
than a polite exercise, and he concludes : " Le calcul des probabilit6s office une 
contradiction dans les termes me"mes qui servent a le designer, et, si je ne crai- 
gnais de rappeler ici un mot trop souvent rgp&e*, je dirais qu'il nous enseigne 
surtout une chose; c'est de savoir que nous ne savons rien." On the other 
hand, the greater part of his book is devoted to working out instances of practi- 
cal application, and he speaks of ' metaphysics ' legitimising particular conven- 
tions. How this comes about is not explained. He seems to endeavour to 
save his reputation as a philosopher by the surrender of probability as a valid 
conception, without at the same time forfeiting his claim as a mathematician 
to work out probable formulae of practical importance. 


requiring for the application of their methods a basis of numerical 
measurement, dwelt on the negative rather than the positive 
side of their evidence, and found it easier to measure equal 
degrees of ignorance than equivalent quantities of experience. 
This led to the explicit introduction of the Principle of Indifference, 
or, as it was then termed, the Principle of Non-Sufficient Eeason. 
The great achievement of the eighteenth century was, in the eyes 
of the early nineteenth, the reconciliation of the two points of 
view and the measurement of probabilities, which were grounded 
on experience, by a method whose logical basis was the Principle 
of Non-Sufficient Reason. This would indeed have been a very 
astonishing discovery, and would, as its authors declared, have 
gradually brought almost every phase of human activity within 
the power of the most refined mathematical analysis. 

But it was not long before more sceptical persons began to 
suspect that this theory proved too much. Its calculations, it 
is true, were constructed from the data of experience, but the 
more simple and the less complex the experience the better satis- 
fied was the theory. What was required was not a wide experi- 
ence or detailed information, but a completeness of symmetry in 
the little information there might be. It seemed to follow from 
the Laplacian doctrine that the primary qualification fox one 
who would be well informed was an equally balanced ignorance. 

6. The obvious reaction from a teaching, which seemed to 
derive from abstractions results relevant to experience, was into 
the arms of empiricism ; and in the state of philosophy at that 
time England was the natural home of this reaction. The first 
protest, of which I am aware, came from Leslie Ellis in 1842. 1 
At the conclusion of his Remarks on an alleged, proof of the Method 
of least squares? " Mere ignorance," he says, " is no ground 
for any inference whatever. Ex niliilo nihil" In Venn's 
Logic of Chance Ellis's suggestions are developed into a complete 
theory : 3 " Experience is our sole guide. If we want to discover 
what is in reality a series of things, not a series of our own concep- 
tions, we must appeal to the things themselves to obtain it, for 
we cannot find much help elsewhere." Professor Edgeworth 4 
was an early disciple of the same school: "The probability," he 

1 On the Foundations of the Theory of Probabilities. 

2 Republished in Miscellaneous Writings. 

3 Logic of Chance, p. 74. 

4 Metretike, p. 4. 


says, " of head occurring n times if the coin is of the ordinary 
make is approximately at least ($) n . This value is rigidly deducible 
from positive experience, the observations made by gamesters, 
the experiments recorded by Jevons and De Morgan." 

The doctrines of the empirical school will be examined in 
Chapter VIII., and I postpone my detailed criticism to that 
chapter. Venn rejects the applications of Bernoulli's theorem, 
which he describes as " one of the last remaining relics of Realism," 
as well as the later Laplacian Law of Succession, thus destroying 
the link between the empirical and the d priori methods. But, 
apart from this, his view that statements of probability are 
simply a particular class of statements about the actual world 
of phenomena, would have led him to a closer dependence on 
actual experience. He holds that the probability of an event's 
having a certain attribute is simply the fraction expressing the 
proportion of cases in which, as a matter of actual fact, this 
attribute is present. Our knowledge, however, of this proportion 
is often reached inductively, and shares the uncertainty to which 
all inductions are liable. And, besides, in referring an event to 
a series we do not postulate that all the members of the series 
should be identical, but only that they should not be known to 
differ in a relevant manner. Even on this theory, therefore, we 
are not solely determined by positive knowledge and the direct 
data of experience. 

7. The Empirical School in their reaction against the preten- 
tious results, which the Laplacian theory affected to develop 
out of nothing, have gone too far in the opposite direction. If 
our experience and our knowledge were complete, we should 
be beyond the need of the Calculus of Probability. And where 
our experience is incomplete, we cannot hope to derive from it 
judgments of probability without the aid either of intuition or of 
some farther d priori principle. Experience, as opposed to in- 
tuition, cannot possibly afford us a criterion by which to judge 
whether on given evidence the probabilities of two propositions 
are or are not equal. 

However essential the data of experience may be, they cannot 

by themselves, it seems, supply us with what we want. Camber, 1 

who prefers what he calls the Principle of Compelling Reason 

(das Prinzip des zwingenden Grundes), and holds that Probability 

1 Wahrscheinlichfaitsrechnung, p. 11. 


has an objective and not merely formal interpretation only when 
it is grounded on definite knowledge, is rightly compelled to 
admit that we cannot get on altogether without the Principle of 
Non-Sufficient Reason. On the grounds both of its own intuitive 
plausibility and of that of some of the conclusions for which it 
is necessary, we are inevitably led towards this principle as a 
necessary basis for judgments of probability. In some sense, 
judgments of probability do seem to be based on equally balanced 
degrees of ignorance. 

8. It is from this starting-point that the German logicians 
have set out. They have perceived that there are few judgments 
of probability which are altogether independent of some principle 
resembling that of Non-Sufficient Reason. But they also appre- 
hend, with Boole, that this may be a very arbitrary method of 

It was pointed out in 18 of Chapter IV. that the cases, in 
which the Principle of Indifference (or Non-Sufficient Reason) 
breaks down, have a great deal in common, and that we break 
up the field of possibility into a number of areas, actually unequal, 
but indistinguishable on the evidence. Several German logicians, 
therefore, have endeavoured to determine some rule by which 
it might be possible to postulate actual equality of area for the 
fields of the various possibilities. 

By far the most complete and closely reasoned solution on 
these lines is that of Von Kries. 1 He is primarily anxious to dis- 
cover a proper basis for the numerical measurement of probabili- 
ties, and he is thus led to examine with care the grounds of valid 
judgments of equiprobability. His criticisms of the Principle 
of Non-Sufficient Reason are searching, and, to meet them, he 
elaborates a number of qualifying conditions which are, he 
argues, necessary and sufficient. The value of his book, however, 
lies, in the opinion of the present writer, in the critical rather 
than in the constructive parts. The manner in which his qualify- 
ing conditions are expressed is often, to an English reader at any 
rate, somewhat obscure, and he seems sometimes to cover up 
difficulties, rather than solve them, by the invention of new 
technical terms. These characteristics render it difficult to 
expound him adequately in a summary, and the reader must be 

1 Die Principien der Wahrscheinlichlceitsrechnung. Eine logische Unter- 
suchung. Freiburg, 1886. 


referred to the original for a proper exposition of the Doctrine of 
Spielrdume. Briefly, but not very intelligibly perhaps, lie may 
be said to hold that the hypotheses for the probabilities of which 
we wish to obtain a numerical comparison, must refer to ' fields ' 
(Spielrdume) which are * indifferent/ ' comparable ' in magnitude, 
and c original ' (ursprunglich). Two fields are ' indifferent ' if 
they are equal before the Principle of Non-Sufficient Reason ; 
they are ' comparable ' if it is true that the fields are actually 
of equal extent ; and they are * original ' or ultimate if they are 
not derived from some other field. The last condition is exceed- 
ingly obscure, but it seems to mean that the objects with which 
we are ultimately dealing must be directly represented by the 
* fields ' of our hypotheses, and there must not be merely correla- 
tion -between these objects and the objects of the fields. The 
qualification of comparability is intended to deal with difficulties 
such as that connected with the population of different areas of 
unknown extent ; and the qualification of originality with those 
arising from indirect measurement, as in the case of specific 

Von Kries's solution is highly suggestive, but it does not seem, 
so far as I understand it, to supply an unambiguous criterion 
for all cases. His discussion of the philosophical character of 
probability is brief and inadequate, and the fundamental error 
in his treatment of the subject is the physical, rather than logical, 
bias which seems to direct the formulation of his conditions. 
The condition of Ursprunglichkeit, for instance, seems to depend 
upon physical rather than logical criteria, and is, as a result, 
much more restricted in its applicability than a condition, which 
will really meet the difficulties of the case, ought to be. But, 
although I differ from him in his philosophical conception of 
probability, the treatment of the Principle of Indifference, which 
fills the greater part of his book, is, I think, along fruitful lines, 
and I have been deeply indebted to it in formulating my own 
conditions in Chapter IV. 

Of less closely reasoned and less detailed treatments, which 
aim at the same kind of result, those of Sigwart and Lotze are 
worth noticing. Sigwart's 1 position is sufficiently explained by 
the following extract : " The possibility of a mathematical treat- 
ment lies primarily in the fact that in the disjunctive judgment 
1 Sigwart, Logic (Eng. edition), vol. ii. p. 220. 


tlie number oi terms in the disjunction plays a decisive part. 
Inasmuch, as a limited number of mutually exclusive possi- 
bilities is presented, of which one alone is actual, the element 
of number forms an essential part of our knowledge. . . . Our 
knowledge must enable us to assume that the particular terms of 
the disjunction are so far equivalent that they express an equal 
degree of specialisation of a general concept, or that they cover 
equal parts of the whole extension of the concept. . . . This 
equivalence is most intuitable where we are dealing with equal 
parts of a spatial area, or equal parts of a period of time. . . . 
But even where this obvious quality is not forthcoming, we may 
ground our expectations upon a hypothetical equivalence, where 
we see no reason for considering the extent of one possibility to 
be greater than that of the others. ..." 

In the beginning of this passage Sigwart seems to be aware 
of the fundamental difficulty, although exception may be taken 
to the vagueness of the phrase " equal degree of specialisation of 
a general concept." But in the last sentence quoted he surrenders 
the advantages he has gained in the earlier part of his explana- 
tion, and, instead of insisting on a knowledge of an equal degree 
of specialisation, he is satisfied with an absence of any knowledge 
to the contrary. Hence, in spite of his initial qualifications, he 
ends unrestrainedly in the arms of Non-Sufficient Keason. 1 

Lotze, 2 in' a brief discussion of the subject, throws out some 
remarks well worth quoting : " We disclaim all knowledge of 
the circumstances which condition the real issue, so that when 
we talk of equally possible cases we can only mean coordinated as 
equivalent species in the compass of an universal case ; that is to 
say, if we enumerate the special forms, which the genus can 
assume, we get a disjunctive judgment of the form : if the con- 
dition B is fulfilled, one of the kinds / a / 2 / 8 ... of the universal 
consequent F will occur to the exclusion of the rest. Which of 
all those different consequents will, in fact, occur, depends in all 
cases on the special form bJ> z b B ... in which that universal 
condition is fulfilled. ... A coordinated case is a case which 
answers to one and only one of the mutually exclusive values 
bfiv ... of the condition B, and these rival values may occur in 

1 Sigwart's treatment of the subject of probability is curiously inaccurate. 
Of his four fundamental rules of probability, for instance, three are, as he states 
them, certainly false. 

2 Lotze, Logic (Eng. edition), pp. 364, 365. 


reality ; it does not answer to a more general form B, of this 
condition, which can never exist in reality, because it embraces 
several of the particular values b^. ..." 

This certainly meets some of the difficulties, and its resem- 
blance to the conditions formulated in Chapter IV. will be evident 
to the careful reader. But it is not very precise, and not easily 
applicable to all cases, to those, for instance, of the measure- 
ment of continuous quantity. By combining the suggestions of 
Von Kries, Sigwart, and Lotze, we might, perhaps, patch up a 
fairly comprehensive rule. We might say, for instance, that if 
& x and & are classes, their members must be finite in number and 
enumerable or they must compose stretches ; that, if they are 
finite in number, they must be equal in number ; and that, if 
their members compose stretches, the stretches must be equal 
stretches ; and that if b l and & 2 are concepts, they must represent 
concepts of an equal degree of specialisation. But qualifications 
so worded would raise almost as many difficulties as they solved. 
How, for instance, are we to know when concepts are of an equal 
degree of specialisation 1 

9. That probability is a relation has often received incidental 
recognition from logicians, in spite of the general failure to place 
proper emphasis on it. The earliest writer, with whom I am 
acquainted, explicitly to notice this, is Kahle in his Elementa 
logicae Probabilium methodo mathematics in usum Scientiarum 
et Vitae adornata published at Halle in 1735. 1 Amongst more 
recent writers casual statements are common to the effect that 
the probability of a conclusion is relative to the grounds upon 
which it is based. Take Boole 2 for instance : " It is implied in 
the definition that probability is always relative to our actual 

1 This work, which seems to have soon fallen into complete neglect and is 
now extremely rare, is full of interest and original thought. The following 
quotations will show the fundamental position taken up : " Est cognitio pro- 
babilis, si desunt quaedam requisita ad veritatem demonstrativam (p. 15). 
Propositio probabilis esse potest falsa, et improbabilis esse potest vera ; ergo 
cognitio hodie possibilis, crastina luce mutari potest improbabilem, si accedunt 
reliqua requisita omnia, in certitudinem (p. 26). . . . Certitudo est terminus 
relatives : considerare potest ratione representationum in intellectu nostro. 
. . . Incerta nobis dependent a defectu cognitionis (p. 35), . . . Actionem 
imprudenter et contra regulas probabilitatis susceptam eventus felix sequi 
potest. Ergo prudentia actionum ex successu solo non est aestimanda (p. 62). 
. . . Logica probabilium est scientia dijudicandi gradum certitudinis eorum, 
quibus desunt requisita ad veritatem demonstratiram (p. 94)." 

2 " On a General Method in the Theory of Probabilities," Phil Mag., 4th 
Series, viii., 1854. See also, " On the Application of the Theory of Probabilities 


state of information and varies with, that state of information. 53 
Or Bradley : 1 " Probability tells us what we ought to believe, 
what we ought to believe on certain data . . . Probability is no 
more ' relative ' and ' subjective ' than is any other act of 
logical inference from hypothetical premises. It is relative to 
the data with which it has to deal, and is not relative in any other 
sense." Or even Laplace, when he is explaining the diversity 
of human opinions : " Dans les choses qui ne sont que vraisem- 
blables, la difference des donne"es que chaque homme a sur elles, 
est une des causes principales de la diversite des opinions que 
Ton voit regner sur les mSmes objets . . . c'est ainsi que le 
me*me fait, recite devant une nombreuse assemblee, obtient divers 
degre"s de croyance, suivant Tetendue des connaissances des 
auditeurs." 2 

10. Here we may leave this account of the various directions 
in which progress has seemed possible, with the hope that it may 
assist the reader, who is dissatisfied with the solution proposed in 
Chapter IV., to determine the line of argument along which he 
is likeliest to discover the solution of a difficult problem. 

to the Question of the Combination of Testimonies or Judgments " (Edin. Phil. 
Trans, xxi. p. 600) : " Our estimate of the probability of an event varies not 
absolutely with the circumstances which actually affect its occurrence, but with 
our knowledge of those circumstances." 

1 The Principles of Logic, p. 208. 

2 Bssai philosophical e, p. 7. 



1. THE theory of probability, outlined in the preceding chapters, 
has serious difficulties to overcome. There is a theoretical, as 
well as a practical, difficulty in measuring or comparing degrees 
of probability, and a further difficulty in determining them 
d priori. We must now examine an alternative theory which is 
much freer from these troubles, and is widely held at the present 

2. The theory is in its essence a very old one. Aristotle 
foreshadowed it when he held that " the probable is that which 
for the most part happens " ; 1 and, as we have seen in Chapter 
VII., an opinion not unlike this was entertained by those philoso- 
phers of the seventeenth and eighteenth centuries who approached 
the problems of probability uninfluenced by the work of mathe- 
maticians. But the underlying conception of earlier writers 
received at the hands of some English logicians during the latter 
half of the nineteenth century a new and much more complicated 

The theory in question, which I shall call the Frequency 
Theory of Probability, first appears 2 as the basis of a proposed 
logical scheme in a brief essay by Leslie Ellis On the Foundations 
of the Theory of Probabilities, and is somewhat further developed 
in his Remarks on the Fundamental Principles of the Theory of 

1 RJiet. i. 2, 1357 a 34. 

2 I give Ellis the priority because Ms paper, published in 1843, was read on 
Feb. 14, 1842. The same conception, however, is to be found in Cournot's 
Exposition, also published in 1843 : "La the"orie des probability's a pour objet 
certains rapports mimeriques qui prendraient des valeurs fixes et comple* tement 
de'termine'es, si Ton pouvait re'pe'ter a 1'infini les e"preuves des mSmes hasards, 
et qui, pour un nombre G d'e*preuves, oscillent entre des limites d'autant plus 
resserre'es, d'autant plus voisines des valeurs finales, que le nombre des e*prcuves 
est plus grand." 



Probabilities. 1 " If the probability of a given event be correctly 
determined," he says, "the event will on a long run of trials tend 
to recur with frequency proportional to their probability. This 
is generally proved mathematically. It seems to me to be true 
d priori. ... I have been unable to sever the judgment that 
one event is more likely to happen than another from the belief 
that in the long run it will occur more frequently." Ellis ex- 
plicitly introduces the conception that probability is essentially 
concerned with a group or series. 

Although the priority of invention must be allowed to Leslie 
Ellis, the theory is commonly associated with the name of Venn. 
In his Logic of Chance 2 it first received elaborate and systematic 
treatment, and, in spite of his having attracted a number of 
followers, there has been no other comprehensive attempt to 
meet the theory's special difficulties or the criticisms directed 
against it. I shall begin, therefore, by examining it in the form 
in which Venn has expounded it. Venn's exposition is much 
coloured by an empirical view of logic, which is not perhaps as 
necessary to the essential part of his doctrine as he himself 
implies, and is not shared by all of those who must be classed as 
in general agreement with him about probability. It will be 
necessary, therefore, to supplement a criticism of Venn by an 
account of a more general frequency theory of probability, 
divested of the empiricism with which he has clothed it. 

3. The following quotations from Venn's Logic of Chance will 
show the general drift of his argument : The fundamental con- 
ception is that of a series (p. 4). The series is of events which 
have a certain number of features or attributes in common (p. 10). 
The characteristic distinctive of probability is this, the occa- 
sional attributes, as distinguished from the permanent, are found 
on an examination to tend to exist in a certain definite proportion 
of the whole number of cases (p. 11). We require that there should 
be in nature large classes of objects, throughout all the individual 
members of which a general resemblance extends. For this 

1 These essays were published in the Transactions of the Camb. Phil. Soo., the 
first in 1843 (vol. viii.), and the second in 1854 (vol. ix.). Both were reprinted 
in Mathematical and other Writings (1863), together with three other brief 
papers on Probability and the Method of Least Squares. All five are full of 
spirit and originality, and are not now so well known as they deserve to be. 

2 The first edition appeared in 1866. Revised editions were issued in 1876 
and 1888. [References are given to the third edition of 1888. 


purpose the existence of natural kinds or groups is necessary 
(p. 55). The distinctive characteristics of probability prevail 
principally in the properties of natural lands, both in the ultimate 
and in the derivative or accidental properties (p. 63). The same 
peculiarity prevails again in the force and frequency of most 
natural agencies (p. 64). There seems reason to believe that it 
is in such things only, as distinguished from things artificial, that 
the property in question is to be found (p. 65). How, in* any 
particular case, are we to establish the existence of a probability 
series 1 Experience is our sole guide. If we want to discover 
what is in reality a series of things, not a series of our own con- 
ceptions, we must appeal to the things themselves to obtain it, 
for we cannot find much help elsewhere (p. 174). When proba- 
bility is divorced from direct reference to objects, as it substanti- 
ally is by not being founded upon experience, it simply resolves 
itself into the common algebraical doctrine of Permutations 
and Combinations (p. 87). By assigning an expectation in 
reference to the individual, we mean nothing more than to make 
a statement about the average of his class (p. 151). When we say 
of a conclusion within the strict province of probability, that it 
is not certain, all that we mean is that in some proportion of 
cases only will such conclusion be right, in the other cases it will 
be wrong (p. 210). 

The essence of this theory can be expressed in a few words. 
To say, that the probability of an event's having a certain charac- 
teristic is -, is to mean that the event is one of a number of events, 
a proportion - of which have the characteristic in question ; and 
the fact, that there is such a series of events possessing this 
frequency in respect of the characteristic, is purely a matter of 
experience to be determined in the same manner as any other 
question of fact. That such series do exist happens to be a 
characteristic of the real world as we know it, and from this 
the practical importance of the calculation of probabilities is 

Such a theory possesses manifest advantages. There is no 
mystery about it no new indefrnables, no appeals to intuition. 
Measurement leads to no difficulties ; our probabilities or fre- 
quencies are ordinary numbers, upon which the arithmetical 
ipparatus can be safely brought to bear. And at the same time it 


seems to crystallise in a clear, explicit shape the floating opinion 
of common sense that an event is or is not probable in certain 
supposed circumstances according as it is or is not usual as a 
matter of fact and experience. 

The two principal tenets, then, of Venn's system are these, 
that probability is concerned with series or groups of events, 
and that all the requisite facts must be determined empirically, 
a statement in probability merely summing up in a convenient 
way a group of experiences. Aggregate regularity combined 
with individual difference happens, he says, to be characteristic 
of many events in the real world. It will often be the case, 
therefore, that we can make statements regarding the average 
of a certain class, or regarding its characteristics in the long run, 
which we cannot make about any of its individual members 
without great risk of error. As our knowledge regarding the 
class as a whole may give us valuable guidance in dealing with an 
individual instance, we require a convenient way of saying that 
an individual belongs to a class in which certain characteristics 
appear on the average with a known frequency ; and this the 
conventional language of probability gives us. The importance 
of probability depends solely upon the actual existence of such 
groups or real kinds in the world of experience, and a judgment 
of probability must necessarily depend for its validity upon oux 
empirical knowledge of them. 

4. It is the obvious, as well as the correct, criticism of such a 
theory, that the identification of probability with statistical 
frequency is a very grave departure from the established use of 
words ; for it clearly excludes a great number of judgments 
which are generally believed to deal with probability. Venn 
himself was well aware of this, and cannot be accused of supposing 
that all beliefs, which are commonly called probable, are really 
concerned with statistical frequency. But some of his followers, 
to judge from their published work, have not always seen, so 
clearly as he did, that his theory is not concerned with the same 
subject as that with which other writers have dealt under the 
same title. Venn justifies his procedure by arguing that no other 
meaning, of which it is possible to take strict logical cognisance, 
can reasonably be given to the term, and that the other meanings, 
with which it has been used, have not enough in common to 
permit their reduction to a single logical scheme. It is useless, 


therefore, for a critic of Venn to point out that many supposed 
judgments of probability are not concerned with statistical 
frequency ; for, as I understand the Logic of Chance, he admits 
it ; and the critic must show that the sense different from Venn's 
in which the term probability is often employed has an important 
logical interpretation about which we can generalise. This 
position I seek to establish. It is, in my opinion, this other sense 
alone which has importance ; Venn's theory by itself has few 
practical applications, and if we allow it to hold the field, we must 
admit that probability is not the guide of life, and that in following 
it we are not acting according to reason. 

5. Part of the plausibility of Venn's theory is derived, I 
think, from a failure to recognise the narrow Emits of its ap- 
plicability 3 or to notice his own admissions regarding this. " In 
every case/ 3 he says (p. 124), "in which we extend our inferences 
by Induction or Analogy, or depend upon the witness of others, 
or trust to our own memory of the past, or come to a conclusion 
through conflicting arguments, or even make a long and com- 
plicated deduction by mathematics or logic, we have a result of 
which we can scarcely feel as certain as of the premisses from 
which it was obtained. In all these cases, then, we are conscious 
of varying quantities of belief, but are the laws according to which 
the belief is produced and varied the same ? If they cannot be 
reduced to one harmonious scheme, if, in fact, they can at best be 
brought to nothing but a number of different schemes, each with 
its own body of laws and rules, then it is vain to endeavour to 
force them into one science.'* All these cases, therefore, in which 
we are * not certain/ Venn explicitly excludes from what he 
chooses to call the science of probability, and he pays no further 
attention to them. The science of probability is, according to 
him, no more than a method which enables us to express in a 
convenient form statistical statements of frequency. " The 
province of probability/' he says again on page 160, " is not so 
extensive as that over which variation of belief might be observed. 
Probability only considers the case in which this variation is 
brought about in a certain definite statistical way." 1 He points 

1 Edgeworth uses the term * probability * widely, as I do ; but he makes 
a distinction corresponding to Venn's by limiting the subject-matter of the 
Calculus of Probabilities. He writes (* Philosophy of Chance,* Mind, 1884, 
p. 223) : " The Calculus of Probabilities is concerned with the estimation of 
degrees of probability ; not every species of estimate, but that which is founded 


out on p. 194 that for the purposes of probability we must take 
the statistical frequency from which we start ready made and 
ask no questions about the process or completeness of its manu- 
facture : " It may be obtained by any of the numerous rules 
furnished by Induction, or it may be inferred deductively, or 
given by our own observation ; its value may be diminished by 
its depending upon the testimony of witnesses, or its being 
recalled by our own memory. Its real value may be influenced 
by these causes or any combinations of them ; but all these are 
preliminary questions with which we have nothing directly to do. 
We assume our statistical proposition to be true, neglecting the 
diminution of its value by the processes of attainment." 

It must be recognised, therefore, that Venn has deliberately 
excluded from his survey almost all the cases in which we regard 
our judgments as ' only probable ' ; and, whatever the value or 
consistency of his own scheme, he has left untouched a wide 
field of study for others. 

6. The main grounds, which have induced Venn to regard 
judgments based on statistical frequency as the only cases of 
probability which possess logical importance, seem to be two : 
(i.) that other cases are mainly subjective, and (ii.) that they 
are incapable of accurate measurement. 

With regard to the first it must be admitted that there are 
many instances in which variation of belief is occasioned by purely 
psychological causes, and that his argument is valid against those 
who have defined probability as measuring the degree of sub- 
jective belief. But this has not been the usual way of 
looking at the subject. Probability is the study of the 
grounds which lead us to entertain a rational preference for 
one belief over another. That there are rational grounds other 
than statistical frequency, for such preferences, Venn does 
not deny; he admits. in the quotation given above that the 
* real vahte ' of our conclusion is influenced by many other con- 
on a particular standard. That standard is the phenomenon of statistical 
uniformity : the fact that a genus can very frequently be subdivided into species 
such that the number of individuals in each species bears an approximately 
constant ratio to the number of individuals in the genus." This use of terms is 
legitimate, though it is not easy to follow it consistently. But, like Venn's, 
it leaves aside the most Important questions. The Calculus of Probabili- 
ties, thus interpreted, is no guide by itself as to which opinion we ought 
to follow, and is not a measure of the weight we should attach to conflicting 




siderations than that of statistical frequency. Venn's theory, 
therefore, cannot be fairly propounded by his disciples as alterna- 
tive to such a theory as is propounded here. For my Treatise is 
concerned with the general theory of arguments from premisses 
leading to conclusions which are reasonable but not certain ; 
and this is a subject which Venn has, deliberately, not treated 
in the Logic of Chance. 

7. Apart from two circumstances, it would scarcely be neces- 
sary to say anything further ; but in the first place some writers 
have believed that Venn has propounded a complete theory 
of .probability, failing to realise that he is not at all concerned 
with the sense in which we may say that one induction or analogy, 
or testimony, or memory, or train of argument is more probable 
than another ; and in the second place he himself has not always 
kept within the narrow limits, which he has himself laid down 
as proper to his theory. 

For he has not remained content with defining a probability 
as identical with a statistical frequency, but has often spoken 
as if his theory told us which alternatives it is reasonable to prefer. 
When he states, for instance, that modality ought to be banished 
from Logic and relegated to Probability (p. 296), he forgets his 
own dictum that of premisses, the distinctive characteristic of 
which is their lack of certainty, Probability takes account of 
one class only, Induction concerning itself with another class, and 
so forth (p. 321). He forgets also that, when he comes to consider 
the practical use of statistical frequencies, he has to admit that 
an event may possess more than one frequency, and that we must 
decide which of these to prefer on extraneous grounds (p. 213). 
The device, he says, must be to a great extent arbitrary, and there 
are no logical grounds of decision ; but would he deny that it is 
often reasonable to found our probability on one statistical 
frequency rather than on another ? And if our grounds are 
reasonable, are they not in an important sense logical ? 

Even in those cases, therefore, in which we derive our prefer- 
ence for one alternative over another from a knowledge of statis- 
tical frequencies, a statistical frequency by itself is insufficient 
to determine us. We may call a statistical frequency a prob- 
ability, if we choose ; but the fundamental problem of deterraining 
which of several alternatives is logically preferable still awaits 
solution. We cannot be content with the only counsel S/enn 


can offer, that we should choose a frequency which is derived 
from a series neither too large nor too small. 

The same difficulty, that a probability in Venn's sense is 
insufficient to determine which alternative is logically preferable, 
arises in another connection. In most cases the statistical 
frequency is not given in experience for certain, but is arrived 
at by a process of induction, and inductions, he admits, are not 
certain. If, in the past, three infants out of every ten have 
died in their first four years, induction may base on this the 
doubtful assertion, All infants die in that proportion. But we 
cannot assert on this ground, as Venn wishes to do, that the prob- 
ability of the death of an infant in its first four years is i^ths. 
We can say no more than that it is probable (in my sense) that 
there is such a probability (in his sense). Tor the purpose of 
coming to a decision we cannot compare the value of this 
conclusion with that of others until we know the probability 
(in my sense) that the statistical frequency really is i%ths. 
The cases in which we can determine the logical value of a 
conclusion entirely on grounds of statistical frequency would 
seem to be extremely few in number. 

8. The second main reason which led Venn to develop his 
theory is to be found in his belief that probabilities which are 
based on statistical frequencies are alone capable of accurate 
measurement. The term ' probabilities,' he argues, is properly 
confined to the case of chances which can be calculated, and all 
calculable chances can be made to depend upon statistical 
frequency. In attempting to establish this latter contention 
he is involved in some paradoxical opinions. " In many cases," 
'he admits, " it is undoubtedly true that we do not resort to direct 
experience at all. If I want to know what is my chance of 
holding ten trumps in a game of whist, I do not enquire how 
often such a thing has occurred before. ... In practice, d priori 
determination is often easy, whilst d posteriori appeal to experi- 
ence would be not merely tedious but utterly impracticable." 
But these cases which are usually based on the Principle of 
Indifference can,, he maintains, be justified on statistical grounds. 
In the case of coin tossing there is a considerable experience of 
the equally frequent occurrence of heads and tails ; the experi- 
ence gained in this simple case is to be extended to the complex 
cases by "Induction and Analogy." In one simple case the 


result to which, the Principle of Indifference would lead is that 
which experience recommends. Therefore in complex cases, 
where there is no basis of experiment at all, we may assume that 
Experience, if experience there was, would speak with the same 
voice as Indifference. This is to assert that, because in one case, 
where there is no known reason to the contrary, there actually 
is none, therefore in other cases incapable of verification the 
absence of known reason to the contrary proves that actually 
there is none. 

The attempt to justify the rules of inverse probability on 
statistical grounds I have failed to understand ; and after a care- 
ful reading, I am -unable to produce an intelligible account of 
the argument involved in the latter part of chapter vii. of the 
Logic of Chance.* I am doubtful whether Venn should not have 
excluded d posteriori arguments in probability from his scheme 
as well as inductive arguments. The attempt to include them 
may have been induced by a desire to deal with all cases 
in which numerical calculation has been commonly thought 

9. The argument so far has been solely concerned with the 
case for the frequency theory developed in the Logic of Chance. 
The criticisms which follow will be directed against a more 
general form of the same theory which may conceivably have 
recommended itself to some readers. It is unfortunate that no 
adherent of the doctrine, with the exception of Venn, has at- 
tempted to present the theory of it in detail. Professor Karl 
Pearson, for instance, probably agrees with Venn in a general 
way only, and it is very likely that many of the foregoing remarks 
do not apply to his view of probability ; but while I generally 
disagree with the fundamental premisses upon which his work 
in probability and statistics seems to rest, I am not clearly 
aware of the nature of the philosophical theory from which he 
bhinka that he derives them and which makes them appear to 
him to be satisfactory. A careful exposition of his logical pre- 
suppositions would greatly add to the completeness of his work, 
[n the meantime it is only possible to raise general objections to 

1 Let the reader, who is acquainted with this chapter, consider what precise 
assumption Venn's reasoning requires on p. 187 in the example which seeks to 
show the efficacy of Lord Lister's antiseptic treatment d posteriori. What is 
;ha 'inevitable assumption about the bags* when it is translated into the 
anguage of this example ? 


any theory of probability which seeks to found itself upon the 
conception of statistical frequency. 

The generalised frequency theory which I propose to put 
forward, as perhaps representative of what adherents of this 
doctrine have in mind, differs from Venn's in several important 
respects. 1 In the first place, it does not regard probability as 
being identical with statistical frequency, although it holds that 
all probabilities must be based on statements of frequency, and 
can be defined in terms of them. It accepts the theory that 
propositions rather than events should be taken as the subject- 
matter of probability; and it adopts the comprehensive view 
of the subject according to which it includes induction and all 
other cases in which we believe that there are logical grounds for 
preferring one alternative out of a set none of which are certain. 
Nor does it follow Venn in supposing any special connection to 
exist between a frequency theory of probability and logical 

10. A proposition can be a member of many distinct classes 
of propositions, the classes being merely constituted by the 
existence of particular resemblances between their members 
or in some such way. We may know of a given proposition that 
it is one of a particular class of propositions, and we may also 
know, precisely or within defined limits, what proportion of this 
class are true, without our being aware whether or not the given 
proposition is true. Let us, therefore, call the actual proportion 
of true propositions in a class the truth-frequency 2 of the class, 
and define the measure of the probability of a proposition relative 
to a class, of which it is a member, as being equal to the truth- 
frequency of the class. 

The fundamental tenet of a 1 frequency theory of probability 
is, then, that the probability of a proposition always depends 
upon referring it to some class whose truth-frequency is known 
within wide or narrow limits. 

Such a theory possesses most of the advantages of Venn's, 
but escapes his narrowness. There is nothing in it so far which, 
could not be easily expressed with complete precision in the 
terms of ordinary logic. Nor is it necessarily confined to prob- 

1 In what follows I am much indebted for some suggestions in favour of the 
frequency theory communicated to me by Dr. Whitehead ; but it is not to be 
supposed that the exposition which follows represents his own opinion. 

2 This is Dr. Whitehead's phrase. 


abilities which are numerical. In some cases we may know the 
exact number which expresses the truth-frequency of our class ; 
but a less precise knowledge is not without value, and we may 
say that one probability is greater than another, without knowing 
how much greater, and that it is large or small or negligible, if 
we have knowledge of corresponding accuracy about the truth- 
frequencies of the classes to which the probabilities refer. The 
magnitudes of some pairs of probabilities we shall be able to 
compare numerically, others in respect of more and less only, 
and others not at aU. A great deal, therefore, of what has been 
said in Chapter III. would apply equally to the present theory, 
with this difference that the probabilities would, as a matter of 
fact, have numerical values in all cases, and the less complete 
comparisons would only hold the field in cases where the real 
probabilities were partially unknown. On the frequency theory, 
therefore, there is an important sense in which probabilities can 
be unknown, and the relative vagueness of the probabilities 
employed in ordinary reasoning is explained as belonging not 
to the probabilities themselves but only to our knowledge of 
them. For the probabilities are relative, not to our knowledge, 
but to some objective class, possessing a perfectly definite truth- 
frequency, to which we have chosen to refer them. 

The frequency theory expounded in this manner cannot easily 
avoid mention of the relativity of probabilities which is implicit 
here, as it is in Venn's. Whether or not the probability of a 
proposition is relative to given data, it is clearly relative to the 
particular class or series to which we choose to refer it. A given 
proposition has a great variety of different probabilities corre- 
sponding to each of the various distinct classes of which it is a 
member ; and before an intelligible meaning can be given to a 
statement that the probability of a proposition is so-and-so, the 
class must be specified to which the proposition is being referred. 
Most adherents of the frequency theory would probably go 
further, and agree that the class of reference must be determined 
in any particular case by the data at our disposal. Here, then, 
is another point on which it is not necessary for the frequency 
theory to diverge from the theory of this Treatise. It should, 
I think, be generally agreed by every school of thought that the 
probability of a conclusion is in an important sense relative to 
given premisses. On this issue and also on the point that our 


knowledge of many probabilities is not numerically definite, 
there might well be for the future an end of disagreement, and 
disputation might be reserved for the philosophical interpretation 
of these settled facts, which it is unreasonable to deny, however 
we may explain them. 

11. I now proceed to those contentions upon which my 
fundamental criticism of the frequency theory is founded. The 
first of these relates to the method by which the class of reference 
is to be determined. The magnitude of a probability is always 
to be measured by the truth-frequency of some class ; and this 
class, it is allowed, must be determined by reference to the 
premisses, on which the probability of the conclusion is to be 
determined. But, as a given proposition belongs to innumerable 
different classes, how are we to know which class the premisses 
indicate as appropriate ? What substitute has the frequency 
theory to offer for judgments of relevance and indifference ? 
And without something of this kind, what principle is there for 
uniquely determining the class, the truth-frequency of which is 
to measure the probability of the argument? Indeed the 
difficulties of showing how given premisses determine the class 
of reference, by means of rules expressed in terms of previous 
ideas, and without the introduction of any notion, which is new 
and peculiar to probability, appear to me insurmountable. 

Whilst no general criterion of choice seems to exist, where of 
two alternative classes neither includes the other, it might be 
thought that where one does include the other, the obvious 
course would be to take the narrowest and most specialised class. 
This procedure was examined and rejected by Venn ; though the 
objection to it is due, not, as he supposed, to the lack of sufficient 
statistics in such cases upon which to found a generalisation, 
but to the inclusion in the class-concept of marks characteristic 
of the proposition in question, but nevertheless not relevant 
to the matter in hand. If the process of narrowing the class 
were to be carried to its furthest point, we should generally be 
left with a class whose only member is the proposition in question, 
for we generally know something about it which is true of no 
other proposition. We cannot, therefore, define the class of 
reference as being the class of propositions of which everything 
is true which is known to be true of the proposition whose prob- 
ability we seek to determine. And, indeed, in those examples 


for which the frequency theory possesses the greatest prima facie 
plausibility, the class of reference is selected by taking account 
of some only of the known characteristics of the quaesitum, those 
characteristics, namely, which are relevant in the circumstances. 
In those cases in which one can admit that the probability can be 
measured by reference to a known truth-frequency, the class of 
reference is formed of propositions about which our relevant 
knowledge is the same as about the proposition under considera- 
tion. In these special cases we get the same result from the 
frequency theory as from the Principle of Indifference. But 
this does not serve to rehabilitate the frequency theory as a 
general explanation of probability, and goes rather to show that 
the theory of this Treatise is the generalised theory, compre- 
hending within it such applications of the idea of statistical truth- 
frequency as have validity. 

* Relevance ' is an important term in probability, of which 
the meaning is readily intelligible. I have given my own defini- 
tion of it already. But I do not know how it is to be explained 
in terms of the frequency theory. Whether supporters of this 
theory have fully appreciated the difficulty I much doubt. It is 
a fundamental issue involving the essence of the peculiarity of 
probability, which prevents its being explained away in terms 
of statistical frequency or anything else. 

12. Yet perhaps a modified view of the frequency theory 
could be evolved which would avoid this difficulty, and I proceed, 
therefore, to some further criticisms. It might be agreed that a 
novel element must be admitted at this point, and that relevancy 
must be determined in some such manner as has been explained 
in earlier chapters. With this admission, it might be argued, the 
theory would still stand, divested, it is true, of some of its original 
simplicity, but nevertheless a substantial theory differing in 
important respects, although not quite so fundamentally as 
before, from alternative schemes. 

The next important objection, then, is concerned with the 
manner in which the principal theorems of probability are to be 
established on a theory of frequency. This will involve an 
anticipation in some part of later arguments ; and the reader 
may be well advised to return to the following paragraph after 
he has finished Part II. 

13. Let us begin by a consideration of the ' Addition Theorem.' 


If a/h denotes the probability of a on hypothesis Ji, this theorem 
may be written (a + b)/h=a/h + b/k-ab/h, and may be read 
' On hypothesis h the probability of " a or b " is equal to the 
probability of a + the probability of 6 - the probability of 
" both a and 6." ' This theorem, interpreted in some way or 
other, is universally assumed ; and we must, therefore, inquire 
what proof of it the frequency theory can afford. A little 
symbolism will assist the argument : Let a 7 represent the truth- 
frequency of any class a, and let ajfi stand for ' the probability 
of a on hypothesis h, a being the class of reference determined 
by this hypothesis/ * "We then have ajh = a f , and we require to 
prove a proposition, for values of 7 and B not yet determined, 
which will be of the form : 

(a + fy s /h = ajh + "bjh - db y fh. 

Now if S' is the class of propositions (a + b) such that a is an 
a and b a /3, it is easily shown by the ordinary arithmetic of classes 
that S f f = a f + /3f - afif where a/3 is the class of propositions which 
are members of both a and /3. In the case, therefore, where 
S = S' and 7 = aj8, an addition theorem of the required kind has 
been established. 

But it does not follow by any reasonable rule that, if h deter- 
mines a and j8 as the appropriate classes of reference for a and &, 
h must necessarily determine S' and a/3 as the appropriate classes 
of reference for (a + b) and ab ; it may, for instance, be the case 
that h, while it renders a and /8 determinate, yields no informa- 
tion whatever regarding a, and points to some quite different 
class /ju as the suitable class of reference for ab. On the frequency 
theory, therefore, we cannot maintain that the addition theorem 
is true in general, but only in those special cases where it happens 
that 8 = $' and 7 = a/3. 

The following is a good example : We are given 
that the proportion of black-haired men in the population 

P J?2 

is -^ and the proportion of colour-blind men , and there is no 

1 * Z 

known connection between black - hair and colour - blindness : 
what is the probability that a man, about whom nothing special 

1 The question, previously at issue, as to how the class of reference is deter- 
mined by the hypothesis, is now ignored. 


is known, is 1 either black-haired or colour-blind ? If we represent 
the hypotheses by h and the alternatives by a and fc, it would 
usually be held that, colour -blindness and black hair being 

independent for knowledge 2 relative to the given data, abjh = -^ ? , 

and that, therefore, by the addition theorem, (a + b)/h-- l + 

- -. But, on the frequency theory, this result might be 

invalid; for a$ s =* - 1 , only if this is the actual proportion in fact 

of persons who are both colour-blind and black-haired, and that 
this is the actual proportion cannot possibly be inferred from 
the independence for knowledge of the characters in question. 3 

Precisely the same difficulty arises in connection with the 
multiplication theorem ab/h^a/bh.b/h.* In the frequency nota- 
tion, which is proposed above, the corresponding theorem will 
be of the form abjh = a y fbh . b^/h. For this equation to be satisfied 
it is easily seen that S must be the class of propositions xy such 
that a? is a member of a and y of /3, and 7 the class of propositions 
xb such that # is a member of a ; and, as in the case of the addition 
theorem, we have no guarantee that these classes 7 and S will be 
those which the hypotheses bh and h will respectively determine 
as the appropriate classes of reference for a and ah. 

In the case of the theorem of inverse probability 5 

II all _ a/bh b/h 
c/ah a/ch c/h 

the same difficulty again arises, with an additional one when 
practical applications are considered. For the relative proba- 
bilities of our d priori hypotheses, 6 and c, will scarcely ever be 
capable of determination by means of known frequencies, and in 
the most legitimate instances of the inverse principle's operation 

1 In the course of the present discussion the disjunctive a + b is never inter- 
preted so as to exclude the conjunctive db. 

2 JFor a discussion of this term see Chapter XVL 2. 

8 Venn argues (Logic of Chance, pp. 173, 174) that there is an inductive 
ground for making this inference. The question of extending the fundamental 
theorems of a frequency theory of probability by means of induction is discussed 
in 14 below. 

4 Vide Chapter XII. 6, and Chapter XIV. 4. 

5 Vide Chapter XIV. 5. 


we depend either upon an inductive argument or upon the 
Principle of Indifference. It is hard to think of an example in 
which the frequency conditions are even approximately satisfied. 

Thus an important class of case, in which arguments in proba- 
bility, generally accepted as satisfactory, do not satisfy the 
frequency conditions given above, are those in which the notion 
is introduced of two propositions being, on certain data, inde- 
pendent for knowledge. The meaning and definition of this 
expression is discussed more fully in Part II. ; but I do not see 
what interpretation the frequency theory can put upon it. Yet 
if the conception of * independence for knowledge ' is discarded, 
we shall be brought to a standstill in the vast majority of problems, 
which are ordinarily considered to be problems in probability, 
simply from the lack of sufficiently detailed data. Thus the 
frequency theory is not adequate to explain the processes of 
reasoning which it sets out to explain. If the theory restricts its 
operation, as would seem necessary, to those cases in which we 
know precisely how far the true members of a and y8 overlap, 
the vast majority of arguments in which probability has been 
employed must be rejected. 

14. An appeal to some further principle is, therefore, required 
before the ordinary apparatus of probable inference can be estab- 
lished on considerations of statistical frequency ; and it may 
have occurred to some readers that assistance may be obtained 
from the principles of induction. Here also it will be necessary 
to anticipate a subsequent discussion. If the argument of Part 
III. is correct, nothing is more fatal than Induction to the theory 
now under criticism. For, so far from Induction's lending 
support to the fundamental rules of probability, it is itself 
dependent on them. In any case, it is generally agreed that 
an inductive conclusion is only probable, and that its probability 
increases with the number of instances upon which it is founded. 
According to the frequency theory, this belief is only justified if 
the majority of inductive conclusions actually are true, and it 
will be false, even on our existing data, that any of them are even 
probable, if the acknowledged possibility that a majority are 
false is an actuality. Yet what possible reason can the frequency 
theory offer, which does not beg the question, for supposing that 
a majority are true ? And failing this, what ground have we 
for believing the inductive process to be reasonable ? Yet we 


invariably assume that with our existing knowledge it is logically 
reasonable to attach some weight to the inductive method, even 
if future experience shows that not one of its conclusions is verified 
in fact. The frequency theory, therefore, in its present form at 
any rate, entirely fails to explain or justify the most important 
source of the most usual arguments in the field of probable 

15. The failure of the frequency theory to explain or justify 
arguments from induction or analogy suggests some remarks of a 
more general kind. While it is undoubtedly the case that many 
valuable judgments in probability are partly based on a know- 
ledge of statistical frequencies, and that many more can be held, 
with some plausibility, to be indirectly derived from them, there 
remains a great mass of probable argument which it would be 
paradoxical to justify in the same manner. It is not sufficient, 
therefore, even if it is possible, to show that the theory can be 
developed in a self -consistent manner ; it must also be shown 
how the body of probable argument, upon which the greater 
part of our generally accepted knowledge seems to rest, can 
be explained in terms of it ; for it is certain that much of 
it does not appear to be derived from premisses of statistical 

Take, for instance, the intricate network of arguments upon 
which the conclusions of The Origin of Species are founded : 
how impossible it would be to transform them into a shape in 
which they would be seen to rest upon statistical frequency ! 
Many individual arguments, of course, are explicitly founded 
upon such considerations ; but this only serves to differentiate 
them more clearly from those which are not. Darwin's own 
account of the nature of the argument may be quoted : " The 
belief in Natural Selection must at present be grounded entirely 
on general considerations : (1) on its being a vera causa, from 
the struggle for existence and the certain geological fact that 
species do somehow change ; (2) from the analogy of change 
under domestication by man's selection ; (3) and chiefly from 
this view connecting under an intelligible point of view a host 
of facts. Wlien we descend to details . - . we cannot prove that 
a single species has changed ; nor can we prove that the supposed 
changes are beneficial, which is the groundwork of the theory ; 
nor can we explain why some species have changed and others 


have not/ 5 I Not only in the main argument, but in many of the 
subsidiary discussions, 2 an elaborate combination of induction 
and analogy is superimposed upon a narrow and limited know- 
ledge of statistical frequency. And this is equally the case in 
almost all everyday arguments of any degree of complexity. 
The class of judgments, which a theory of statistical frequency 
can comprehend, is too narrow to justify its claim to present a 
complete theory of probability. 

16. Before concluding this chapter, we should not overlook 
the element of truth which the frequency theory embodies and 
which provides its plausibility. In the first place, it gives a 
true account, so long as it does not argue that probability and 
frequency are identical, of a large number of the most precise 
arguments in probability, and of those to which mathematical 
treatment is easily applicable. It is this characteristic which 
has recommended it to statisticians, and explains the large 
measure of its acceptance in England at the present time ; for 
the popularity in this country of an opinion, which has, so far 
as I know, no thorough supporters abroad, may reasonably be 
attributed to the chance which has led most of the English 
writers, who have paid much attention to probability in recent 
years, to approach the subject from the statistical side. 

In the second place, the statement that the probability of an 
event is measured by its actual frequency of occurrence c in the 
long run ' has a very close connection with a valid conclusion 
which can be derived, in certain eases, from Bernoulli's theorem. 
This theorem and its connection with the theory of frequency will 
be the subject of Chapter XXIX. 

17. The absence of a recent exposition of the logical basis of 
the frequency theory by any of its adherents has been a great 
disadvantage to me in criticising it. It is possible that some 
of the opinions, which I have examined at length, are now held 
by no one ; nor am I absolutely certain, at the present stage of 
the inquiry, that a partial rehabilitation of the theory may not 
be possible. But I am sure that the objections which I have 
raised cannot be met without a great complication of the theory, 
and without robbing it of the simplicity which is its greatest 

1 Letter to G. Bentham, Life and Letters, vol. iii. p. 25. 

2 E.g. in the discussion on the relative effect of disuse and selection in 
reducing unnecessary organs to a rudimentary condition. 


preliminary recommendation. Until the theory has been given 
new foundations, its logical basis is not so secure as to permit 
controversial applications of it in practice. A good deal of 
modern statistical work may be based, I think, upon an incon- 
sistent logical scheme, which, avowedly founded upon a theory 
of frequency, introduces principles which this theory has no 
power to justify. 



1. THAT part of our knowledge which we obtain directly, 
supplies the premisses of that part which we obtain by argument. 
From these premisses we seek to justify some degree of rational 
beUef about all sorts of conclusions. We do this by perceiv- 
ing certain logical relations between the premisses and the 
conclusions. The kind of rational belief which we infer in 
this manner is termed probable (or in the limit certain), and the 
logical relations, by the perception of which it is obtained, we 
term relations of probability. 

The probability of a conclusion a derived from premisses h 
we write ajh ; and this symbol is of fundamental importance. 

2. The object of the Theory or Logic of Probability is to 
systematise such processes of inference. In particular it aims 
at elucidating rules by means of which the probabilities of different 
arguments can be compared. It is of great practical importance 
to determine which of two conclusions is on the evidence the 
more probable. 

The most important of these rules is the Principle of 
Indifference. According to this Principle we must rely upon 
direct judgment for discriminating between the relevant and 
the irrelevant parts of the evidence. We can only discard 
those parts of the evidence which are irrelevant by seeing that 
they have no logical bearing on the conclusion. The irrelevant 
evidence being thus discarded, the Principle lays it down that 
if the evidence for either conclusion is the same (i.e. symmetrical), 
then their probabilities also are the same (i.e. equal). 

If, on the other hand, there is additional evidence (i.e. in 
addition to the symmetrical evidence) for one of the conclusions, 
and this evidence is favourably relevant, then that conclusion is 



the more probable. Certain rules have been given by which to 
judge whether or not evidence is favourably relevant. And by 
combinations of these judgments of preference with the judg- 
ments of indifference warranted by the Principle of Indifference 
more complicated comparisons are possible. 

3. There are, however, many cases in which these rules 
furnish no means of comparison ; and in which it is certain that 
it is not actually within our power to make the comparison. It 
has been argued that in these cases the probabilities are, in fact, 
not comparable. As in the example of similarity, where there 
are different orders of increasing and diminishing similarity, but 
where it is not possible to say of every pair of objects which of 
them is on the whole the more like a third object, so there are 
different orders of probability, and probabilities, which are not 
of the same order, cannot be compared. 

4. It is sometimes of practical importance, when, for example, 
we wish to evaluate a chance or to determine the amount of 
our expectation, to say not only that one probability is greater 
than another, but by how much it is greater. We wish, that is 
to say, to have a numerical measure of degrees of probability. 

This is only occasionally possible. A rule can be given for 
numerical measurement when the conclusion is one of a number 
of equiprobable, exclusive, and exhaustive alternatives, but not 

5. In Part II. I proceed to a symbolic treatment of the 
subject, and to the greater systematisation, by symbolic methods 
on the basis of certain axioms, of the rules of probable argument. 

In Parts III., IV., and V. the nature of certain very important 
types of probable argument of a complex kind will be treated 
in detail ; in Part III. the methods of Induction and Analogy, 
in Part IV. certain semi-philosophical problems, and in Part V. 
the logical foundations of the methods of inference now com- 
monly known as statistical. 






1. IN Part I. we Lave been occupied with, the epistemology of our 
subject, that is to say, with what we know about the characteristics 
and the justification of probable Knowledge. In Part II. I pass 
to its Formal Logic. I am not certain of how much positive value 
this Part will prove to the reader. My object in it is to show 
that, starting from the philosophical ideas of Part L, we can 
deduce by rigorous methods out of simple and precise definitions 
the usually accepted results, such as the theorems of the addition 
and multiplication of probabilities and of inverse probability. 
The reader will readily perceive that this Part would never have 
been written except under the influence of Mr. Russell's Principia 
Mathematica. But I am sensible that it may suffer from the 
over-elaboration and artificiality of this method without the 
justification which its grandeur of scale affords to that great work. 
In common, however, with other examples of formal method, 
this attempt has had the negative advantage of compelling the 
author to make his ideas precise and of discovering fallacies and 
mistakes. It is a part of the spade-work which a conscientious 
author has to undertake ; though the process of doing it may 
be of greater value to frrm than the results can be to the reader, 
who is concerned to know, as a safeguard of the reliability of the 
rest of the construction, that the thing can be done, rather than 
to examine the architectural plans in detail. In the development 
of my own thought, the following chapters have been of great 
importance. For it was through trying to prove the fundamental 
theorems of the subject on the hypothesis that Probability was 
a relation that I first worked my way into the subject ; and the 
rest of this Treatise has arisen out of attempts to solve the 
successive questions to which the ambition to treat Probability 
as a branch of Formal Logic first gave rise. 



A further occasion of diffidence and apology in introducing 
this Part of my Treatise arises out of the extent of my debt to 
Mr. W. E. Johnson. I worked out the first scheme in complete 
independence of his work and ignorant of the fact that he had 
thought, more profoundly than I had, along the same lines ; I 
have also given the exposition its final shape with my own hands. 
But there was an intermediate stage, at which I submitted what 
I had done for his criticism, and received the benefit not only of 
criticism but of his own constructive exercises. The result is 
that in its final form it is difficult to indicate the exact extent of 
my indebtedness to him. When the following pages were first 
in proof, there seemed little likelihood of the appearance of any 
work on Probability from his own pen, and I do not now proceed 
to publication with so good a conscience, when he is announcing 
the approaching completion of a work on .Logic which will include 
" Problematic Inference." ** 

I propose to give here a brief summary of the five chapters 
following, without attempting to be rigorous or precise. I shall 
then be free to write technically in Chapters XL -XV., inviting 
the reader, who is not specially interested in the details of this 
sort of technique, to pass them by. 

2. Probability is concerned with arguments, that is to say, 
with the " bearing " of one set of propositions upon another set. 
If we are to deal formally with a generalised treatment of this 
subject, we must be prepared to consider relations of probability 
between any pair of sets of propositions, and not only between 
sets which are actually the subject of knowledge. But we soon 
find that some limitation -must be put on the character of sets of 
propositions which we can consider as the hypothetical subject 
of an argument, namely, that they must be possible subjects of 
knowledge. We cannot, that is to say, conveniently apply our 
theorems to premisses which are self -contradictory and formally 
* inconsistent with themselves. 

For the purpose of this limitation we have to make a distinc- 
tion between a set of propositions which is merely false in fact 
and a set which is formally inconsistent with itself. 1 This leads 

1 Spinoza had in mind, I think, the distinction between Truth and Prob- 
ability in his treatment of Necessity, Contingenco, and Possibility. Res 
enim omnes ex data Dei natura neceasario seguutae sunt, et ex necessitate naturae 
Dei determinate sunt ad certo modo existendum et operandum (Mhices i. 33). 
That is to say, everything is, -without qualification, true or false. At res 


us to the conception of a group of propositions, which, is defined 
as a set of propositions such that (i.) if a logical principle 
belongs to it, all propositions which are instances of that logical 
principle also belong to it ; (ii.) if the proposition p and the 
proposition ' not-p or q ' both belong to it, then the proposition 
q also belongs to it ; (iii.) if any proposition p belongs to it, then 
the contradictory of p is excluded from it. If the group defined 
by one part of a set of propositions excludes a proposition which 
belongs to a group defined by another part of the set, then the 
set taken as a whole is inconsistent with itself and is incapable of 
forming the premiss of an argument. 

The conception of a group leads on to a precise definition of 
one proposition requiring another (which in the realm of assertion 
corresponds to relevance in the realm of probability), and of logical 
priority as being an order of propositions arising out of their 
relation to those special groups, or real groups, which are in fact 
the subject of knowledge. Logical priority has no absolute 
signification, but is relative to a specific body of knowledge, or, 
as it has been termed in the traditional logic, to the Universe of 

It also enables us to reach a definition of inference distinct from 
implication, as defined by Mr. Russell. This is a matter of very 
great importance. Readers who are acquainted with the work 
of Mr. Russell and his followers will probably have noticed that 
the contrast between his work and that of the traditional logic 
is by no means wholly due to the greater precision and more 
mathematical character of his technique. There is a difference 
also in the design. His object is to discover what assumptions 
are required in order that the formal propositions generally 
accepted by mathematicians and logicians may be obtainable 

aligua nulla alia de causa contingens dicitur, nisi respectu defectus nostrae 
cognitionis (Eihices L 33, scholium). That is to say, Contingence, or, as I 
term it, Probability, solely arises out of the limitations of our knowledge. 
Contingence in this "wide sense, which includes every proposition which, in 
relation to our knowledge, is only probable (this term covering all intermediate 
degrees of probability), may be further divided into Contingence in the strict 
sense, which corresponds to an a priori or formal probability exceeding zero, 
and Possibility ; that is to say, into formal possibility and empirical possibility. 
Res singulares voco contingentes, guatenus, dum ad earum solam essentiam 
attendimus, nihil invenimus, quod earum existentiam necessario ponat, vel 
quod ipsam necessario sedudat. Easdem res singulares voco possibiles, guatenus, 
dum ad causas, ex guibus produci debent, attendimus, nescimus, an ipsae 
determinatae sint ad easdem producendum (Mhices iv. Def 3, 4). 


as the result of successive steps or substitutions of a few very 
simple types, and to lay bare by this means any inconsistencies 
which may exist in received results. But beyond the fact that 
the conclusions to which he seeks to lead up are those of common 
sense, and that the uniform type of argument, upon the validity 
of which each step of his system depends, is of a specially obvious 
kind, he is not concerned with analysing the methods of valid 
reasoning which we actually employ. He concludes with 
familiar results, but he reaches them from premisses, which have 
never occurred to us before, and by an argument so elaborate that 
our minds have difficulty in following it. As a method of setting 
forth the system of formal truth, which shall possess beauty, 
inter-dependence, and completeness, his is vastly superior to 
any which has preceded it. But it gives rise to questions about 
the relation in which ordinary reasoning stands to this ordered 
system, and, in particular, as to the precise connection between 
the process of inference, in which the older logicians were princi- 
pally interested but which he ignores, and the relation of implica- 
tion on which his scheme depends. 

* p implies q ' is, according to his definition, exactly equivalent 
to the disjunction ' q is true or p is false.' If q is true, e p implies 
q ' holds for all values of p ; and similarly if p is false, the im- 
plication holds for all values of q. This is not what we mean 
when we say that q can be inferred or follows from p. For what- 
ever the exact meaning of inference may be, it certainly does not 
hold between all pairs of true propositions, and is not of such a 
character that every proposition follows from a false one. It is 
not true that ' A male now rules over England ' follows or can be 
inferred from e A male now rules over France ' ; or 'A female now 
rules over England ' from ' A female now rules over France 3 ; 
whereas, on Mr. Russell's definition, the corresponding implica- 
tions hold simply in virtue of the facts that c A male now rules 
over England ' is true and ' A female now rules over France * 
is false. 

The distinction between the Relatival Logic of Inference and 
Probability, and Mr. Russell's Universal Logic of Implication, 
seems to be that the former is concerned with the relations of 
propositions in general to a particular limited group. Inference 
and Probability depend for their importance upon the fact that 
in actual reasoning the limitation of our knowledge presents us 


with, a particular set of propositions, to which we must relate any 
other proposition about which we seek knowledge. The course 
of an argument and the results of reasoning depend, not simply 
on what is true, but on the particular body of knowledge from 
which we have set out. Ultimately, indeed, Mr. Russell cannot 
avoid concerning himself with groups. For his aim is to discover 
the smallest set of propositions which specify our formal know- 
ledge, and then to show that they do in fact specify it. In this 
enterprise, being human, he must confine himself to that part of 
formal truth which we know, and the question, how far his 
axioms comprehend all formal truth, must remain insoluble. 
But his object, nevertheless, is to establish a train of implications 
between formal truths ; and the character and the justification of 
rational argument as such is not his subject. 

3. Passing on from these preliminary reflections, our first 
task is to establish the axioms and definitions which are to make 
operative our symbolical processes. These processes are almost 
entirely a development of the idea of representing a probability 
by the symbol ajh, where h is the premiss of an argument and a 
its conclusion. It might have been a notation more in accord- 
ance with our fundamental ideas, to have employed the symbol 
a/Ji to designate the argument from h to a, and to have represented 
the probability of the argument, or rather the degree of rational 
belief about a which the argument authorises, by the symbol 
P(a/A). This would correspond to the symbol V(a/i) which has 
been employed in Chapter VI. for the evidential value of the 
argument as distinct from its probability. But in a section 
where we are only concerned with probabilities, the use of P(a/h) 
would have been unnecessarily cumbrous, and it is, therefore, 
convenient to drop the prefix P and to denote the probability 
itself by a/A. 

The discovery of a convenient symbol, like that of an essential 
word, has often proved of more than verbal importance. Clear 
thinking on the subject of Probability is not possible without a 
symbol which takes an explicit account of the premiss of the 
argument as well as of its conclusion ; and endless confusion has 
arisen through discussions about the probability of a conclusion 
without reference to the argument as a whole. I claim, therefore, 
the introduction of the symbol a/h as an essential step towards 
any progress in the subject. 


4. Inasmuch, as relations of Probability cannot be assumed 
to possess the properties of numbers, the terms addition and 
multiplication of probabilities have to be given appropriate 
meanings by definition. It is convenient to employ these 
familiar expressions, rather than to invent new ones, because the 
properties which arise out of our definitions of addition and 
multiplication in Probability are analogous to those of addition 
and multiplication in Arithmetic. But the process of establishing 
these properties is a little complicated and occupies the greater 
part of Chapter XII./ 

The most important of the definitions of Chapter XII. are the 
following (the numbers referring to the numbers of Chapter 
XII.) : 

II. The Definition of Certainty : a/h = l. 

III. The Definition of Impossibility : a/h = Q. 

VI. The Definition of Inconsistency : ah is inconsistent if 

VII. The Definition of a Group : the class of propositions a 
such that a/h = 1 is the group h. 

VIII. The Definition of Equivalence : if b/ah = 1 and a/bh = 1 

IX. The Definition of Addition: 

X. The Definition of Multiplication: ab/h^afbh . b/h = 
b/ah . a/h. The symbolical development of the subject largely 
proceeds out of these definitions of Addition and Multiplication. 
It is to be observed that they give a meaning, not to the addition 
and multiplication of any pairs of probabilities, but only to pairs 
which satisfy a certain form. The definition of Multiplication 
may be read : ' the probability of both a and 6 given h is equal 
to the probability of a given bh, multiplied by the probability of 
b given h. 9 

XI. The Definition of Independence: if a l /a 2 h = a l /h and 
ajajh^a^h, a^/h and ajh are independent. 

XII. The Definition of Irrelevance: if a 1 /a 2 h=a- i /h i a 2 is 
irrelevant to a^/h. 

5. In Chapter XIII. these definitions, supplemented by a few 
axioms, are employed to demonstrate the fundamental theorems 
of Certain or Necessary Inference. The interest of this chiefly 
lies in the fact that these theorems include those which the 

1 b stands for the contradictory of 6. 


traditional Logic has termed the Laws of Thought, as for example 
the Law of Contradiction and the Law of Excluded Middle. 
These are here exhibited as a part of the generalised theory 
of Inference or Eational Argument, which includes probable 
Inference as well as certain Inference. The object of this chapter 
is to show that the ordinarily accepted rules of Inference can in 
fact be deduced from the definitions and axioms of Chapter XII. 

6. In Chapter XIV. I proceed to the fundamental Theorems 
of Probable Inference, of which the following are the most 
interesting : 

Addition Theorem : (a + b)/h = a/h + bfh - abjh, which reduces 
to (a -t- b)[h = a/h + b/h, where a and b are mutually exclusive ; 
and, if p^p 2 . . . p n form, relative to h, a set of exclusive and 


exhaustive alternatives, a/h=^p r a/h. 


Theorem of Irrdevance : If ajhji^^afh^, then a/hji 2 = a/h i ' s 

^e. if a proposition is irrelevant, its contradictory also is irrelevant. 

Theorem of Independence : If a z /a 1 h=a 2 /h 3 a 1 /a 2 h=a 1 /h; i.e. 

if % is irrelevant to a^h, it follows that a 2 is irrelevant to a^fh 

and that a^/h and a 2 /h are independent. 

Multiplication Theorem: If a^/h and ajh are independent, 
a^jh . a z /h. 

Theorem of Inverse Probability : =-L_L. . -*l. Further, 

if a 1 /h=p l9 a2/A=y 2 , bfa- L h=q- L , b/a z h = q 2y and 

then aJbh=* ^^ ; and if aJh = aJh, aJbh= ^ , which 

Pi9 r i+? 2 ?2 .. Il+ft 

is equivalent to the statement that the probability of % when 

we know b is equal to ^ 9 where j x is the probability of b when 

we know a^ and y 2 its probability when we know a 2 . This 
theorem enunciated with varying degrees of inaccuracy appears 
in all Treatises on Probability, but is not generally proved. 

Chapter XIV. concludes with some elaborate theorems on the 
combination of premisses based on a technical symbolic device, 
known as the Cumulatwe Formula, which is the work of Mr. W. E. 

7. In Chapter XV. I bring the non-numerical theory of 
probability developed in the preceding chapters into connection 
with the usual numerical conception of it, and demonstrate how 


and in what class of cases a meaning can be given to a numerical 
measure of a relation of probability. Tins leads on to what 
may be termed numerical approximation, that is to say, the 
relating of probabilities, which are not themselves numerical, 
to probabilities, which are numerical, by means of greater and less, 
by which in some cases numerical limits may be ascribed to 
probabilities which are not capable of numerical measures. 



1. THE Theory of Probability deals with the relation between 
two sets of propositions, such that, if the first set is known to be 
true, the second can be known with the appropriate degree of 
probability by argument from the first. 1 The relation, however, 
also exists when the first set is not known to be true and is hypo- 

In a symbolical treatment of the subject it is important 
that we should be free to consider hypothetical premisses, and 
to take account of relations of probability as existing between 
any pair of sets of propositions, whether or not the premiss is 
actually part of knowledge. But in acting thus we must be 
careful to avoid two possible sources of error. 

2. The first is that which is liable to arise wherever variables 
are concerned. This was mentioned in passing in 18 of Chapter 
IV. We must remember that whenever we substitute for a 
variable some particular value of it, this may so affect the relevant 
evidence as to modify the probability. This danger is always 
present except where, as in the first half of Chapter XIII., the 
conclusions respecting the variable are certain. 

3. The second difficulty is of a different character. Our 
premisses may be hypothetical and not actually the subject of 
knowledge. But must they not be possible subjects of know- 
ledge ? How are we to deal with hypothetical premisses which 
are self -contradictory or formally inconsistent with themselves, 
and which cannot be the subject of rational belief of any degree ? 

1 Or more strictly, " perception of -which, together wfch knowledge of the 
first set, justifies an appropriate degree of rational belief about the second." 



Whether or not a relation of probability can be held to exist 
between a conclusion and a self-inconsistent premiss, it will be 
convenient to exclude such relations from our scheme, so as to 
avoid having to provide for anomalies which can have no interest 
in an account of the actual processes of valid reasoning. Where 
a premiss is inconsistent with itself it cannot be required. 

4. Let us term the collection of propositions, which are 
logically involved in the premisses in the sense that they follow 
from them, or, in other words, stand to them in the relation of 
certainty, 1 the group specified by the premisses. That is to say, 
we define a group as containing all the propositions logically 
involved in any of the premisses or in any conjunction of them ; 
and as excluding all the propositions the contradictories of which 
are logically involved in any of the premisses or in any con- 
junction of them. 2 To say, therefore, that a proposition follows 
from a premiss, is the same thing as to say that it belongs to the 
group which the premiss specifies. 

The idea of a c group ' will then enable us to define ' logical 
consistency.' If any part of the premisses specifies a group 
containing a proposition, the contradictory of which is contained 
in a group specified by some other part, the premisses are logically 
inconsistent ; otherwise they are logically consistent. In short, 
premisses are inconsistent if a proposition * follows from ' one 
part of them, and its contradictory from another part. 

5. We have still, however, to make precise what we mean in 
this definition by one proposition fo llo winy from or being logically 
involved in the truth of another. We seem to intend by these 
expressions some kind of transition by means of a logical principle. 
A logical principle cannot be better defined, I think, than in terms 
of what in Mr. Russell's Logic of Implication is termed a formal 
implication. e p implies q ' is a formal implication if ' not-^> or q ' 
is formally true ; and a proposition is formally true, if it is a value 
of a prepositional function, in which all the constituents other 

1 ' a can be inferred from &/ ' a follows from 6,' * a is certain in relation to 
6,' * a is logically involved in 6,' I regard as equivalent expressions, the precise 
meaning of which, will be defined in succeeding paragraphs. " a is implied by V 
I use in a different sense, namely, in Mr. Russell's sense, as the equivalent of 
'# ornot-a.' 

2 For the conception of a group, and for many other notions and definitions 
in the course of this chapter those, for example, of a real group and of 
logical priority I am largely indebted to Mr. W. E. Johnson. The origination 
of the theory of groups is due to him. 


than the arguments are logical constants, and of which all the 
values are true. 

We might define a group in such a way that all logical principles 
belonged to every group. In this case all formally true proposi- 
tions would belong to every group. This definition is logically 
precise and would lead to a coherent theory. But it possesses 
the defect of not closely corresponding to the methods of reasoning 
we actually employ, because all logical principles are not in fact 
known to us. And even in the case of those which we do know, 
there seems to be a logical order (to which on the above definition 
we cannot give a sense) amongst propositions, which are about 
logical constants and are formally true, just as there is amongst 
propositions which are not formally true. Thus, if we were to 
assume the premisses in every argument to include all formally 
true propositions, the sphere of probable argument would be 
limited to what (in contradistinction to formally true propositions) 
we may term empirical propositions. 

6. For this reason, therefore, I prefer a narrower definition 
which shall correspond more exactly to what we seem to mean 
when we say that one proposition follows from another. Let us 
define a group of propositions as a set of propositions such that : 

(i.) if the proposition ' p is formally true 5 belongs to the group, 
all propositions which are instances of the same formal proposi- 
tional function also belong to it ; 

(ii.) if the proposition p and the proposition * p implies q ' 
both belong to it, then the proposition q also belongs to it ; 

(iii.) if any proposition p belongs to it, then the contradictory 
of p is excluded from it. 

According to this definition all processes of certain inference 
are wholly composed of steps each of which is of one of two simple 
types (and if we like we might perhaps regard the first as com- 
prehending the other). I do not feel certain that these conditions 
may not be narrower than what we mean when we say that one 
proposition follows from another. But it is not necessary for the 
purpose of defining a group, to dogmatise as to whether any other 
additional methods of inference are, or are not, open to us. If 
we define a group as the propositions logically involved in the 
premisses in the above sense, and prescribe that the premisses of 
an argument in probability must specify a group not less extensive 
than this, we are placing the minimum amount of restriction upon 


the form of our premisses. If, sometimes or as a rule, our 
premisses in fact include some more powerful principle of argu- 
ment, so much the better. 

In the formal rules of probability which follow, it will be 
postulated that the set of propositions, which form the premiss 
of any argument, must not be inconsistent. The premiss must, 
that is to say, specify a group * in the sense that no part of the 
premiss must exclude a proposition which follows from another 
part. But for this purpose we do not need to dogmatise as to 
what the criterion is of inference or certainty. 

7. It will be convenient at this point to define a term which 
expresses the relation converse to that which exists between a 
set of propositions and the group which they specify. The pro- 
positions Pip 2 p n are said to be fundamental to the group 
h if (i.) they themselves belong to the group (which involves their 
being consistent with one another) ; (ii.) if between them they 
completely specify the group ; and (iii.) if none of them belong 
to the group specified by the rest (for if p r belongs to the group 
specified by the rest, this term is redundant). 

"When the fundamental set is uniquely determined, a group h f 
is a sub-group to the group h, if the set fundamental to h r is 
included in the set fundamental to h. 

Logically there can be more than one distinct set of proposi- 
tions fundamental to a given group ; and some extra-logical test 
must be applied before the fundamental set is determined uniquely. 
On the other hand, a group is completely determined when the 
constituent propositions of the fundamental set are given. 
Further, any consistent set of propositions evidently specifies 
some group, although such a set may contain propositions 
additional to those which are fundamental to the group it specifies. 
It is clear also that only one group can be specified by a given 
set of consistent propositions. The members of a group are, 
we may 'say, rationally bound up with the set of propositions 
fundamental to it. 

8. If Mr. Bertrand Russell is right, the whole of pure 
mathematics and of formal logic follows, in the sense defined 
above, from a small number of primitive propositions. The 
group, therefore, which is specified by these primitive pro- 
positions, includes the most remote deductions not only amongst 
those known to mathematicians, but amongst those which time 


and skill have not yet served to solve. If we define certainty 
in a logical and not a psychological sense, it seems necessary, 
if our premisses include the essential axioms, to regard as 
certain all propositions which follow from these, whether or 
not they are known to us. Yet it seems as if there must 
be some logical sense in which improved mathematical 
theorems some of those, for instance, which deal with the 
theory of numbers -can be likely or unlikely, and in which a 
proposition of this kind, which has been suggested to us by 
analogy or supported by induction, can possess an intermediate 
degree of probability. 

There can be no doubt, I think, that the logical relation of 
certainty does exist in these cases in which lack of skill or insight 
prevents our apprehending it, in spite of the fact that sufficient 
premisses, including sufficient logical principles, are known to us. 
In these cases we must say, what we are not permitted to say 
when the indeterminacy arises from lack of premisses, that the 
probability is unknown. There is still a sense, however, in which 
in such a case the knowledge we actually possess can be, in a 
logical sense, only probable. While the relation of certainty 
exists between the fundamental axioms and every mathematical 
hypothesis (or its contradictory), there are other data in relation 
to which these hypotheses possess intermediate degrees of 
probability. If we are unable through lack of skill to discover 
the relation of probability which an hypothesis does in fact bear 
towards one set of data, this set is practically useless, and we must 
fix our attention on some other set in relation to which the prob- 
ability is not unknown. When Newton held that the binomial 
theorem possessed for empirical reasons sufficient probability 
to warrant a further investigation of it, it was not in relation to 
the axioms of mathematics, whether he knew them or not, that 
the probability existed, but in relation to his empirical evidence 
combined, perhaps, with some of the axioms. There is, in short, 
an exception to the rule that we must always consider the prob- 
ability of any conclusion in relation to the whole of the data in 
our possession. When the relation of the conclusion to the whole 
of our evidence cannot be known, then we must be guided by 
its relation to some part of the evidence* When, therefore, in 
later chapters I speak of a formal proposition as possessing an 
intermediate degree of probability, this will always be in relation 


to evidence from which the proposition does not logically follow 
in the sense defined in 6. * 

9. It follows from the preceding definitions that a proposition 
is certain in relation to a given premiss, or, in other words, follows 
from this premiss if it is included in the group which that premiss 
specifies. It is impossible if it is excluded from the group if , 
that is to say, its contradictory follows from the premiss. We 
often say, somewhat loosely, that two propositions are contra- 
dictory to one another, when they are inconsistent in the sense 
that, relative to our evidence, they cannot belong to the same 
group. On the other hand, a proposition, which is not itself 
included in the group specified by the premiss and whose contra- 
dictory is not included either, has in relation to the premiss an 
intermediate degree of probability. 

If a follows from h and is, therefore, included in the group 
specified by A, this is denoted by ajh = 1. The relation of certainty, 
that is to say, is denoted by the symbol of unity. The reason 
why this notation is useful and has been adopted by common 
consent will appear when -the meaning of the product of a pair 
of relations of probability has been explained. If we represent 
the relation of certainty by 7 and any other probability by 
a, the product a . <y = a. Similarly, if a is excluded from the 
group specified by h and is impossible in relation to it, this is 
denoted by a/A=0. The use of the symbol zero to denote 
impossibility arises out of the fact that, if <o denotes impossibility 
and a any other relation of probability, then, in the senses of 
multiplication and addition to be defined later, the product 
a . G) co, and the sum a + a> = a. Lastly, if a is not included 
in the group specified by A, this is written a/h^l or a/h<l: 
and if it is not excluded, this is written ajh^O or a/h>Q. 

10. The theory of groups now enables us to give an account, 
with the aid of some further conceptions, of logical priority and 
of the true nature of inference. The groups, to which we refer 
the arguments by which we actually reason, are not arbitrarily 
chosen. They are determined by those propositions of which 
we have direct knowledge. Our group of reference is specified 
by those direct judgments in which we personally rationally 
certify the truth of some propositions and the falsity of others. 
So long as it is undetermined, or not determined uniquely, 
which propositions are fundamental, it is not possible to discover 


a necessary order amongst propositions or to show in what way 
a true proposition f follows from ' one true premiss rather than 
another. But when we have determined what propositions are 
fundamental, by selecting those which we know directly to be true, 
or in some other way, then a meaning can be attached to priority 
and to the distinction between inference and implication. When 
the propositions which we know directly are given, there is a 
logical order amongst those other propositions which we know 
indirectly and by argument. 

11. It will be useful to distinguish between those groups which 
are hypothetical and those of which the fundamental set is known 
to be true. We will term the former hypothetical groups, and the 
latter real groups. To the real group, which contains all the 
propositions which are known to be true, we may assign the old 
logical term Universe of Reference. While knowledge is here 
taken as the criterion of a real group, what follows will be equally 
valid whatever criterion is taken, so long as the fundamental set 
is in some manner or other determined uniquely. 

If it is impossible for us to know a proposition p except by 
inference from a knowledge of q, so that we cannot know p to be 
true unless we already know q, this may be expressed by saying 
that ' p requires q. 9 More precisely requirement is defined as 
follows : 

p does not require q if there is some real group to which p 
belongs and q does not belong, i.e. if, there is a real group h 
such that p/h = I, q/h=tl ; hence 

p requires q if there is no real group to which p belongs 
and q does not belong. 

p does not require q within the group h, if the group h, to which 
p belongs, contains a subgroup l h r to which p belongs and q does 
not belong ; i.e. if there is a group h r such that h'/h = l, p/h' =1, 
q/h'^1. This reduces to the proposition next but one above 
if h is the Universe of Eeference. In 13 these definitions 
will be generalised to cover intermediate degrees of prob- 

12. Inference and logical priority can be defined in terms of 
requirement and real groups. It is convenient to distinguish 
two types of inference corresponding to hypothetical and real 

1 Subgroups have only been defined, it must be noticed (see 7 above) when 
the fundamental set of the group has been, in some way, uniquely determined. 



groups i.e. to cases where the argument is only hypothetical, 
and cases where the conclusion can be asserted : 

Hypothetical Inference. ' If p, q,' which may also be read 
6 q is hypotheticaily inferrible from p,* means that there is a 
real group h such that q/ph = l, and q/h=$=I. In order that this 
may be the case, ph must specify a group ; i.e. p/h*Q, or in 
other words p must not be excluded from h. Hypothetical 
inference is also equivalent to : ' p implies q,' and c p implies 
q ' does not require ' q.' In other words, q is hypotheticaily 
inferrible from p, if we know that q is true or p is false and if 
we can know this without first knowing either that q is true or 
that p is false. 

Assertoric Inference. ' p .-. q, 9 which may be read ' p therefore 
q * or c q may be asserted by inference from p,' means that * if p, q ' 
is true, and in addition e p ' belongs to a real group ; i.e. there 
are proper groups h and h' such that p/h = l, q/ph f =1, q/h'*l, 
and p jh' 4= 0. 

p is prior to q when p does not require q, and q requires p, 
when, that is to say, we can know p without knowing q, but 
not q unless we first know p. 

p is prior to q within the group h when p does not require q 
within the group, and q does require p within the group. 

It follows from this and from the preceding definitions that, 
if a proposition is fundamental in the sense that we can only 
know it directly, there is no proposition prior to it ; and, more 
generally, that, if a proposition is fundamental to a given 
group, there is no proposition prior to it within the group. 

13. We can now apply the conception of requirement to 
intermediate degrees of probability. The notation adopted is, 
it will be remembered, as follows : 

p/h = a means that the proposition p has the probable relation 
of degree a to the proposition h ; while it is postulated that h is 
self-consistent and therefore specifies a group. 

pfh = l means that p follows from h and is, therefore, in- 
cluded in the group specified by h. 

p/h =0 means that 2? is excluded from the group specified by h. 

If h specifies the Universe of Reference, i.e. if its group com- 
prehends the whole of our knowledge, p/h is called the absolute 
probability of p, or (for short) the probability of p ; and if p/h = 1 
and h specifies any real group, p is said to be absolutely certain 


or (for short) certain. Thus p is ' certain J if it is a member of a 
real group, and a ' certain * proposition is one which we know 
to be true. Similarly if p/h=Q under the same conditions, p is 
absolutely impossible, or (for short) impossible. Thus an 'im- 
possible ' proposition is one which we know to be false. 

The definition of requirement, when it is generalised so as to 
take account of intermediate degrees of probability, becomes, it 
will be seen, equivalent to that of relevance : 

The probability of p does not require q within the group h, if 
there is a subgroup Ti such that, for every subgroup Ji" which 
includes h r and is included in h (i.e. h'/k" = l,h"/h = l),p/h" =p/h f , 
and q/h f =t= q/h. 

When p is included in the group h, this definition reduces to 
the definition of requirement given in 11. 

14. The importance of the theory of groups arises as soon as 
we admit that there are some propositions which we take for 
granted without argument, and that all arguments, whether 
demonstrative or probable, consist in the relating of other con- 
clusions to these as premisses. 

The particular propositions, which are in fact fundamental 
to the Universe of Reference, vary from time to time and from 
person to person. Our theory must also be applicable to hypo- 
thetical Universes. Although a particular Universe of Reference 
may be defined by considerations which are partly psychological, 
when once the Universe is given, our theory of the relation in 
which other propositions stand towards it is entirely logical. 

The formal development of the theory of argument from 
imposed and limited premisses, which is attempted in thefollowing 
chapters, resembles in its general method other parts of formal 
logic. We seek to establish implications between our primitive 
axioms and the derivative propositions, without specific reference 
to what particular propositions are fundamental in our actual 
Universe of Reference. 

It will be seen more clearly in the following chapters that the 
laws of inference are the laws of probability, and that the former 
is a particular case of the latter. The relation of a proposition to 
a group depends upon the relevance to it of the group, and a 
group is relevant in so far as it contains a necessary or sufficient 
condition of the proposition, or a necessary or sufficient condition 
of a necessary or sufficient condition, and so on ; a condition 


being necessary if every hypothetical group, which includes the 
proposition together with the Universe of Reference, includes 
the condition, and sufficient if every hypothetical group, which 
includes the condition together with the Universe of Reference, 
includes the proposition. 



1. IT is not necessary for the validity of what follows to decide 
in what manner the set of propositions is determined, which is 
fundamental to our Universe of Reference, or to make definite 
assumptions as to what propositions are included in the group 
which is specified by the data. When we are investigating an 
empirical problem, it will be natural to include the whole of 
our logical apparatus, the whole body, that is to say, of 
formal truths which are known to us, together with that part 
of our empirical knowledge which is relevant. But in the 
following formal developments, which are designed to display 
the logical rules of probability, we need only assume that our data 
always include those logical rules, of which the steps of our 
proofs are instances, together with the axioms relating to prob- 
ability which we shall enunciate. 

The object of this and the chapters immediately following is 
to show that all the usually assumed conclusions in the funda- 
mental logic of inference and probability follow rigorously from 
a few axioms, in accordance with the fundamental conceptions 
expounded in Part I. This body of axioms and theorems 
corresponds, I think, to what logicians have termed the Laws of 
TlwugTity when they have meant by this something narrower than 
the whole system of formal truth. But it goes beyond what has 
been usual, in dealing at the same time with the laws of probable, 
as well as of necessary, inference. 

2. This and the following chapters of Part II. are largely 
independent of many of the more controversial issues raised in 
the preceding chapters. They do not prejudge the question as 



to whether or not all probabilities are theoretically measurable ; 
and they are not dependent on our theories as to the part played 
by direct judgment in establishing relations of probability or 
inference between particular propositions. Their premisses are 
all hypothetical. Given the existence of certain relations of 
probability, others are inferred. Of the conclusions of Chapter 
III., of the criteria of equiprobability and of inequality discussed 
in Chapters IV. and V., and of the criteria of inference discussed 
in 5, 6 of Chapter XI., they are, I think, wholly independent. 
They deal with a different part of the subject, not so closely 
connected with epistemology. 

3. In this chapter I confine myself to Definitions and Axioms. 
Propositions will be denoted by small letters, and relations 

by capital letters. In accordance with common usage, a dis- 
junctive combination of propositions is represented by the sign 
of addition, and a conjunctive combination by simple juxta- 
position (or, where it is necessary for clearness, by the sign of 
multiplication) : e.g. ' a or b or c ' is written * a + b +c, 5 and * a 
and b and c ' is written ' abc.' e a + b ' is not so interpreted as to 
exclude ' a and &.' The contradictory of a is written a. 

4. Preliminary Definitions : 

I. If there exists a relation of probability P between the 
proposition a and the premiss h 

a/h=? Dei 

II. If P is the relation of certainty l 

P=l Def. 

III. If P is the relation of impossibility 1 

P=0 Def. 

IV. If P is a relation of probability, but not the relation of 
certainty P<1. Def. 

V. If P is a relation of probability, but not the relation of 
impossibility P>0. Def. 

VI. If a/A=0, the conjunction ah is inconsistent. Def. 

VII. The class of propositions a such that a/h = l is the 
group specified by h or (for short) the group h. Def. 

VHL If b/ah = 1 and a/bh = 1, (asb)/h = 1 . Def. 

This may be regarded as the definition of Equivalence. Thus 
we see that equivalence is relative to a premiss h. a is equivalent 
to b, given h, if b follows from ah, and a from bh. 

1 These symbols were first employed by Leibnitz. See p. 155 below. 


5. Preliminary Axioms : 

We shall assume that there is included in every premiss with 
which we are concerned the formal implications which allow us 
to assert the following axioms : 

(i.) Provided that a and h are propositions or conjunctions 
of propositions or disjunctions of propositions, and that h is not 
an inconsistent conjunction, there exists one and only one rela- 
tion of probability P between a as conclusion and li as premiss. 
Thus any conclusion a bears to any consistent premiss h one and 
only one relation of probability. 

(ii.) If (&=&)/& = 1, and # is a proposition, x/ah=x/bh. This 
is the Axiom of Equivalence. 

(iii.) (a + b=d5)/h = l 

(aa=a)/h = 1 

If a/h = 1, ah=h. That is to say, 

if a is included in the group specified by h, h and ah are 

6. Addition and Multiplication. If we were to assume that 
probabilities are numbers or ratios, these operations could be 
given their usual arithmetical signification. In adding or 
multiplying probabilities we should be simply adding or multi- 
plying numbers. But in the absence of such an assumption, it 
is necessary to give a meaning by definition to these processes. 
I shall define the addition and multiplication of relations of 
probabilities only for certain types of such relations. But it 
will be shown later that the limitation thus placed on our opera- 
tions is not of practical importance. 

We define the sum of the probable relations ab/h and afi/h 
as being the probable relation a/h ; and the product of the probable 
relations a/bh and b/h as being the probable relation abjh. That 
is to say : 

IX. ab/h+aB/h=ajh. Def. 

X. db/h = a/bh . b/h = b/ah . a/h. Def. 
Before we proceed to the axioms which will make these sym- 

bols operative, the definitions may be restated in more familiar 
language. IX. may be read : " The sum of the probabilities 
of e both a and b ' and of e a but not &,' relative to the same 
hypothesis, is equal to the probability of 'a' relative to this hypo- 


thesis." X. may be read : " The probability of ' both a and 6,' 
assuming h, is equal to the product of the probability of 6, assum- 
ing h, and the probability of a, assuming both b and h." Or in 
the current terminology z we should have: "The probability 
that both of two events will occur is equal to the probability of 
the first multiplied by the probability of the second, assuming 
the occurrence of the first." It is, in fact, the ordinary rule for 
the multiplication of the probabilities of events which are not 
e independent.' It has, however, a much more central position 
in the development of the theory than has been usually recognised. 
Subtraction and division are, of course, defined as the inverse 
operations of addition and multiplication : 

XI. IfPQ=R,P = ? Del 

XII. If P + Q=E, P=R-Q. Def. 

Thus we have to introduce as definitions what would be axioms 
if the meaning of addition and multiplication were already defined. 
In this latter case we should have been able to apply the ordinary 
processes of addition and multiplication without any further 
axioms. As it is, we need axioms in order to make these symbols, 
to which we have given our own meaning, operative. "When 
certain properties are associated, it is often more or less arbitrary 
which we take as defining properties and which we associate 
with these by means of axioms. In this case I have found it 
more convenient, for the purposes of formal development, to 
reverse the arrangement which would come most natural to 
commonsense, full of preconceptions as to the. meaning of addition 
and multiplication. I define these processes, for the theory of 
probability, by reference to a comparatively rmffl.rmIia.T- property, 
and associate the more familiar properties with this one by means 
of axioms. These axioms are as follows : 

(iv.) If P, Q, R are relations of probability such that the 
products PQ, PR and the sums P + Q, P + R exist, then : 

(iv. a) If PQ exists, QP exists, and PQ = QP. If P + Q exists, 
Q+P exists andP + Q = Q+P. 

(iv.ft) PQ<P unless Q = l or P = 0; P + Q>P unless Q-0. 
PQ = P if Q = l orP-0; P + Q=P if Q-0. 

(iv. o) If PQ|PR, then Q|R unless P = 0. If P + Qf P + R, 
then Q*R and conversely. 

1 E.g. Bertrand, Cakul des probability, p. 26. 


A meaning lias not been given, it is important to notice, to 
the signs of addition and multiplication between probabilities 
in all cases. According to the definitions we have given, P + Q 
and PQ have not an interpretation whenever P and Q are 
relations of probability, but in certain conditions only. Further- 
more, if P + Q=R and Q=S+T, it does not follow that 
P+S+T=R, since no meaning has been assigned to such an 
expression as P + S + T. The equation must be written P -f (S + T) 
=R, and we cannot infer from the foregoing axioms that 
(P + S)+T=R. The following axioms allow us to make this 
and other inferences in cases in which the sum P + S exists, i.e. 
when P +S =A and A is a relation of probability. 

(v.) [PQ] + [BS] = [PR] - [TQTS] = [PR] + 


in every case in which the probabilities [PQ], [RS], 
[PR], etc., exist, i.e., in which these sums satisfy the con- 
ditions necessary in order that a meaning may be given to them 
in the terms of our definition. 

(vi.) P(RS)=PRPS, if the sum RS and the products 
PR and PS exist as probabilities. 

7. From these axioms it is possible to derive a number of 
propositions respecting the addition and multiplication of prob- 
abilities. They enable us to prove, for instance, that if P + Q = 
R+S then P-R=S-Q, provided that the differences P-R 
and S -Q exist ; and that (P + Q) (R +S) = (P + Q)R + (P + Q)S = 
[PR + QR] + [PS + QS] - [PR + QS] + [QR +PS], provided that 
the sums and products in question exist. In general any re- 
arrangement which would be legitimate in an equation between 
arithmetic quantities is also legitimate in an equation between 
probabilities, provided that our initial equation and the equation 
which finally results from our symbolic operations can both be 
expressed in a form which contains only products and sums which 
have an interpretation as probabilities in accordance with the 
definitions. If, theref ore, this condition is observed, we need not 
complicate our operations by the insertion of brackets at every 
stage, and no result can be obtained as a result of leaving them 
out, if it is of the form prescribed above, which could not be 
obtained if they had been rigorously inserted throughout. We 
can only be interested in our final results when they deal with 
actually existent and intelligible probabilities for our object is, 


always, to compare one probability with another and we are 
not incommoded, therefore, in our symbolic operations by the 
circumstance that sums and products do not exist between 
every pair of probabilities. 

8. Independence : 

XTTI. If ajaji=a-jh and a 2 /aji=a z ]h. ) the probabilities 
ajh and a%/h are independent. Def . 

Thus the probabilities of two arguments having the same 
premisses are independent, if the addition to the premisses of the 
conclusion of either leaves them unaffected. 

Irrelevance : x 

XIV. If a I /a^i=aJh, a 2 is irrelevant on the whole, or, for 
short, irrelevant to a-Jh. Def. 

1 This is repeated for convenience of reference from Chapter IV. 14. It is 
only necessary here to take account of irrelevance on the whole, not of the more 
precise sense. 



1. IN this chapter we shall be mainly concerned with deducing 
the existence of relations of certainty or impossibility, given other 
relations of certainty or impossibility, with the rules, that is to 
say, of Certain or, as De Morgan termed it, of Necessary Inference. 
But it will be convenient to include here a few theorems dealing 
with intermediate degrees of probability. Except in one or two 
important cases I shall not trouble to translate these theorems 
from the symbolism in which they are expressed, since their 
interpretation presents no difficulty. 

2. (1) a/h + alh =1. 

For ab/h + db/h = b/h by IX., 

ajbh . bjk + d/bh . b/h - b/h by X. 

Put b/h - 1, then ajbh + d/bh = 1 by (iv. b), 

since b/h = l, bh==h by (iii). 

Thus a/h+d/h = l by (ii.). 

(1.1) If afh=*I, d/h = Q, 

a/h + a/h=l by (1), 

/. ajh + djh = a/k = a/k + by (iv. b) , 

/. a/7t=0 by (iv. c). 

(1.2) Similarly, if a/k = l, a/7i=Q. 

(1.3) If a/A = 0, a/h = l, 

a/7i + djh = l by (1), 

/. +djh =04-1 by (iv. 6), 

/. d/k = l by (iv. c). 

(1.4) Similarly, if d/k =0, a/h = I. 

(2) a/A<l or a/A = l by IV. 

(3) a/h>0 01 a/k=Q by V., 
i.e. there are no negative probabilities. 


(4) ab/h<b/h or ab/h = b/h by X. and (iv. 6). 

(5) If P and Q are relations of probability and P + Q = 0, 
then P=0 and Q=0. 

P + Q>P unless Q=0 by (iv. 6), 

and P>0 unless P =0 by V. 

.*. P + Q>0 unless Q=0, 
Hence, if P + Q=0, Q=0 and similarly P = 0. 

(6) If PQ = 0, P=0 or Q-0, 

Q>0 unless Q=0 by V. 

Hence PQ>P . unless Q =0 or P =0 by (iv. c), 

i.e. PQ>0 unless Q=0 or P = by (iv. &). 

Whence, if PQ=0 3 the result follows. 

(7) If PQ-1, P-l and Q = l, 

PQ<P unless P = or Q = 1 by (iv. 6), 

PQ =P if P =0 or Q = 1 by (iv. 6), 

and P<1 unless P = l by IV., 

/. PQ<1 unless P = l. 
Hence P = 1 ; FriTn.i1fl.r1y Q = 1. 

(8) If a/h=Q, ab/h=Q and a/bh = if bh is not incon- 

For ab/h =b/ah . a/h^a/bk . b/k by X. ? 

and since a/k=0, b/ah . a/h = Q ' by (iv. &), 

/. db/h = and a/bk . b[7i=Q, 

.\ unless bJh=Q, a/bh = by (5), 

whence the result by VI. 

Thus, if a conclusion is impossible, we may add to the con- 
clusion or add consistently to the premisses without affecting the 

(9) If a/h = l, a/bh = l if bh is not inconsistent. 

Since a/Al, alh=0 by (1.1), 

.*. a/bh = Q by (8) if bh is not inconsistent, 

whence a/bk = l by (1.4). 

Thus we may add to premisses, which make a conclusion 
certain, any other premisses not inconsistent with them, without 
affecting the result. 

(10) If a/h - 1, ab/h = b/ah = bfh, 

ab/h = b/ah . a/h = a/bh . b/h by X. 

Since a/h = I 3 a/bh = l by (9) unless b/h=Q, 

.*. b/ah . a/h = b/ah and a/bh . bfh = b]h by (iv. 6), 
whence the result, unless b/h = 0. 


If 6/7* = 0, the result follows from (8). 

(11) If ob/h^l, a/h = l. 

For ab/h = b/ak . a/h by X., 

.'. a/A-1 by (7). 

(12) If (a=b)/h = 1 , a/h = b/h, 

bfah . a/h = a/bh . b/h by X. 

and b/ah = 1, a/bh = 1 by VEX, 

.-. a/h=b/h by (iv. i). 

(12.1) If (a=b)/h = l and 7z# is not inconsistent, 

a/hx = b/hx. 
ajhx . x/h^xfah . afh, 

and &/A# . x/h =x/bh . b/h by X., 

x/ah=x/bh by (ii.) 3 

and a/h = b/h by (12), 

/. a/hx = b/hx unless x/h=Q. 

This is the principk of equivalence. In virtue of it and of 
axiom (ii.), if (a=b)/h=I, we can substitute a for 6 and vice versa, 
wherever they occur in a probability whose premisses include h. 

(13) a/a = I, unless a is inconsistent. 

For a/a = aa/a=*a/aa . a/a by (iii.), (12), and X., 

whence a/aa = I by (ii.), unless a/a = Q, 

i.e. a/a = l, unless a is inconsistent by (iii.), (12), and VI. 

(13.1) a/#=0, unless a is inconsistent. This follows from 
(13) and (l.i). 

(13.2) #/a=0, unless a is inconsistent. This follows from 
(iii.) by writing d for a in (13.1). 

(14) If a/b=Q and a is not inconsistent, 6/a = 0. 

Let /be the group of assumptions, common to a and&, which 
we have supposed to be included in every real group ; 
then a/b=a/bf and b/a = b/af by (iii.) and (12), 

and *lbf.blf = b/af. a/f by X. 

Since a/bf=Q by hypothesis, 

and #//=*= 0, since a is not inconsistent, 

whence b/a = 0. 

Thus, if a is impossible given b y then 6 is impossible given a. 

(15) If AI/*- AiV*" * 

&J.&2/A =hjh 2 h . 7^2/h by n., 

and since 7^2 = 0, hjhjb=0 by (8), unless A/76 2 = 0, whence 
the result by (iv. 6), unless 


If 7^2=0,7^ = by (14), 

since we assume that Ji is not inconsistent, and hence 

A^a/A-0 by (8). 

Thus, if A! is impossible given h 2 , hji 2 is always impossible and is 
excluded from every group. 

(15.1) If 7/, 1 7i 2 /7i=0 and li^i is not inconsistent, k-Jh z 7i=0. 
This, which is the converse of (15), follows rom X. and (6). 

(16) If V/^M^-f >)//> = 1, 

O by (15), 

l by (1.3), 

.-. (Aa+^/A-l by (12) and (iii.). 

(16.1) We may write (16) : 

If h-Jk z = l, (h 2 z>hj)/h = l, where c =>' symbolises e implies.' 
Thus if h follows from h 2 , then it is always certain that 
2 implies Ji^. 

(16.2) If (h^+H^IJi = 1 and 7i 2 7t is not inconsistent, 

Q 9 as in (16), 
/. JiJh 2 h=Q by (15.1), since Jiji is not inconsistent, 

/. hjhji, = l by (1.4). 

This is the converse of (14). 
(16.3) "We may write (16.2) : 

If (h z z>h^pi = I and hji is not inconsistent, Ji-Jb 2 Jt = l. 
Thus, if we define a * group ' as a set of propositions, which follow 
from and are certain relatively to the proposition which specifies 
them, this proposition proves that, if 7* 2 r>&! and h% belong to a 
group kjiy then A x also belongs to this group. 

(17) If (hi D : a^fy/Ji = 1 and h-Ji is not inconsistent, a/h-Ji 
= b/hji. This foUows from (16.3) and (12). 

(18) a/a = l or a/a -1. 

#/# = !, unless < is inconsistent, by (13). 
If a is inconsistent, a/h = 0, where h is not inconsistent, and 
therefore a/h = 1 by (1 .3). 

Thus unless a is inconsistent, a is not inconsistent, and therefore 

a/3-1 by (13). 

(19) aa/A=0, 

a/a = l or ^/a = l by (18), 

/. a/a-0 or a/a = by (1,1) and (1.2). 
In either case oa/A=0 by (15). 


Thus it is impossible that both a and its contradictory 
should be true. This is the Law of Contradiction. 
(20) (a + a)/A = l. 

Since (aa=a + a)/h = 1 by (iii.) 9 

" by (19) and (12), 

by (1.3). 

Thus it is certain that either a or its contradictory is true. This 
is the Law of Excluded Middle. 

(21) If a/hi = l and a/h z = Q, hJt^h^Q. 
For a/AjA 2 . h-Jh 2 = h-Jali z . a/A 2 , 

and a/A]A 2 ^a/Aj. = ^2/^1 5/Ai by X., 

/. afhjhz . 7^7^2 = and d/hji 2 . 
since, by hypothesis and (1), 5/7^ = and a/ 

.-. ajh-Ji^ = Q or 7?. 1 /7z- 2 =0, 
and a/7^2 = 1 or 7^ t = 0, 

/. 7^7^ = or 7^2/7^ = 0. 
In either case 7t 1 74 2 /A=0 by (15). 

Thus, if a proposition is certain relatively to one set of 
premisses, and impossible relatively to another set, the two sets 
are incompatible. 

(22) If a/hi = Q and 7i-Jli = l, a/k=Q, 

=Q by (15), .'. Aj/aA . a/A = 0, 

I by (9), unless a/h=Q. 
.'. in any case a/7t=0. 

(23) If &/a-0 and &/5 = 0, &/7^ = 0. 

a&/A = and o&/A = by (15), 

/. a/bh = Q or &/A = 0, 

and 5/&7&-0 or J/A = by II. and (iv.), 

whence &/A=0 by (1.4). 



1. I SHALL give proofs in this chapter of most of the fundamental 
theorems of Probability, with very little comment. The bearing 
of some of them mil be discussed more fully in Chapter XVI. 

2. The Addition Theorems : 

(24) (a + b)[h = a/k + blh-ab/h. 

In IX. write (a + b) for a, and ab for I. 
Then (a + b)db/h + (a + b)b/h = (a + b)/h, 

whence ab/h + (a + b)(a + 5)Jh = (a + b)/h by (iii.), 

djlli . b/h -f a/h = (a + b)/h by (iii.) and IX. 
That is to say, (a + l}jh = a/h + (1 - a/bJi) . b/7i, 

In accordance with the principles of Chapter XII. 6, this 
should be written, strictly, in the form a]h + (bfh - ab/h), or in 
the form b/h + (a/h-ab/h}. The argument is valid, since the 
probability (b/h-ab/K) is equal to ab/h, as appears from the 
preceding proof, and, therefore, exists. This important theorem 
gives the probability of e a or b * relative to a given hypothesis 
in terms of the probabilities of a,' '&/ and e a and b' relative to 
the same hypothesis. 

(24.1) If a6/^=0, i.e. if a and b are exclusive alternatives 
relative to the hypothesis, then 

(GL + b)/h = a/h + bfh. 

This is the ordinary rule for the addition of the probabilities of 
exclusive alternatives. 

(24.2) ab/h+db/h = b/h, 

since ab+ab=b by (iii.), 

and aab/h=Q by (19) and (8). 

(24.3) (a + b)/h = a/h + ba/h. This follows from (24) and 



(24.4) (a + 6 + e)/A = (a + 6)/A + c/A - (ac + 6c)/A 

= ajh + 1 pi + c/7t - aJ/7& - 6c/A - ca 

(24.5) And in general 

(24.6) Hp^p t /h = for all pairs of values of 5 and Z, it follows 
by repeated application of X. that 


(24.7) If p^ptlli = 0, etc., and (^ +^ 2 + . . . +p n )/h = 1, i.e. 
if 2 } -LPz- - -Pn form, relatively to A, a set of exclusive and 
exhaustive alternatives, then 

(25) If p-$> z . . .p n form, relative to h, a set of exclusive 
and exhaustive alternatives, 

Since (^ +^ 2 + . - . +p H )/h = 1 by hypothesis, 

-" (Pi + ^2 + - +Pn)l a h l ^ (9) if #/& is not inconsistent ; 
and since p s pjh = by hypothesis, 

by (9), if ah is not inconsistent. 

Hence ^p,/ a * = (Pi +Pz + - + Pn)/ah by (24.6) 


= 1. 

Also 3VI/7& =p r /ah . /A. 


Summing ^p r a]k == a/A . *p r /ah, 

, if 7t is not inconsistent, 

If ah is inconsistent, i.e. if a/A = (for A is by hypothesis con- 
sistent), the result follows at once by (8). 

(25.1) If >,.a/A=X,., the above may be written 


(26) a]h 

For (a + A)/A = a/h -t- fi/h - A/A by (24), 

= a/A by (13.1) and (8). 

(26.1) This may be written 

(27) If 

a/A + [&/A - ab/h] = 0, by (24) and hypothesis 

/. ft/A=0 by (v.). 

(27.1) If a/A = and 6/A=0, (a + 6)/A = 0. This follows 
from (24). 

(28) Ha/A-1, (a + 5)/A = l, 

(a + 5)/A = a/A + fo/A by (24.3), 

whence (a + 5)/A = a/A = 1 by (l.l) and (8), together with the 
hypothesis. That is to say, a certain proposition is implied by 
every proposition. 

(28.1) If a/A = 0, (a + 6)/A = l by substituting a for a and 6 
for 5 in (28). That is to say, a certainly false proposition 
implies every proposition. 

(29) If a/ 

and .-. a + AaJ/Aj-O by (15). 

Hence ShJ^O by (27), 

whence the result. 

(29.1) If a/A x =l and a/Ii^ = l 9 a/(A 1 + 7z, 2 ) = l. 
As in (20) ahi](hi + 7& 2 ) = and dhj(h^ + A 2 ) = 0. 

Hence a(7^ + A 2 )/(A! + A a ) = by (27.1), 

whence the result. 

(29.2) If /(&! + ^ 0, 0/7^=0. This foUows from (29). 

(29.3) If a/h^O and a/7i a = 0, a/(A 1 + 7z 2 )=0. This follows 
from (29.1). 

3. Irrelevance and Independence : 

(30) If a/A 1 7fc. 2 = a/7t 1 , then a/A 1 J 2 = ^/A 1 , if A^ is not incon- 

by (24.2), 

whence a/h^^a/h^ unless ^/A^O, i.6. if A^ is not in- 


Thus, if a proposition is irrelevant to an argument, then the 
contradictory of the proposition is also irrelevant. 

(31) If a^aji = a^jh and aji is not inconsistent, a^jaji^ajh. 
This follows by (iv. c), since aja-^h.ajh^a-ja^.ajh by X. 

If, that is to say, % is irrelevant to the argument ajh (see 
XIV.), and a 2 is not inconsistent with h : then a 2 is irrelevant 
to the argument a-Jh ; and a-Jk and aj[h are independent 
(see XIII.). 

4. Theorems of Relevance : 

(32) If a/hh >a/h, hjah >lijh. 

ah is consistent since, otherwise, a/hh l = a/h 0. 
Therefore a/h . hjah = a/hh^ . hjh by X., 

>a/A . firjh by hypothesis : 

so that h 1 /ah>h 1 /h. 

Thus if A! is favourably relevant to the argument a/h, a is 
favourably relevant to the argument hjh. 

This constitutes a formal demonstration of the generally 
accepted principle that if a hypothesis helps to explain a 
phenomenon, the fact of the phenomenon supports the reality 
of the hypothesis. 

In the following theorems p will be said to be more 

favourable to a/h, than q is to b/h, if -->~, i-e. if, in the 

a/h o/h 

language of 8 below, the coefficient of influence of p on ajh 
is greater than the coefficient of influence of q on &/A. 

(33) If x is favourable to a/h, and \ is not less* favourable 
to a/hx than x is to ajhh^ then h-^ is favourable to a/h. 

For a/J^-a/A . . . and by hypothesis the 

a/h a/hx a/hh^x 

second term on the right is greater than unity and the pro- 
duct of the third and fourth terms is greater than or equal 
to unity. 

(33.1) A fortiori, if x is favourable to a/h and not favour- 
able to a/hh^, and if h : is not unfavourable to a/hx, then h^ is 
favourable to a/h. 

(34) If x is favourable to afh, and \ is not less favourable 
to x/ha than x is to h^/ha, then h^ is favourable to a/h. 

This follows by the same reasoning as (33), since by an 
application of the Multiplication Theorem 


a/hl^x a/hh^ xjJih^a h-Jha 
a/hx ' a/hh^x x/ha ' h^/hax 

(35) If x is favourable to a/h, but not more favourable to it 
than la-fl, is, and not less favourable to it than to a/hh^ then 
JI-L is favourable to ajh. 

I? m I-L I a P l a/hh-tx} I a/hx a/hh-,} 

For ahh^ah . \-L . J l.Ji. '_i ' 

I a/kx a/h j \ a/h a/hh-^xj 

This result is a little more substantial than the two 
preceding. By judging the influence of x and Ti^x on the 
arguments afh and afhh l9 we can infer the influence of \ by 
itself on the argument a/A. 


5. The Multiplication Theorems : 

(36) If ajh and ajh are independent, a^ajli = 

For c^tta/A = a-Ja z h . a^h = a^a^li . a-Jh by X., 

and since ajh and 2/7i are independent^ 

aja^h a^h and a^aj/i = ajh by XIII. 
Therefore a l a. 2 /li = a 1 /h . a^li. 

Hence, when ajh and a 2 /A are independent, we can arrive at the 
probability of a^ and # 2 jointly on the same hypothesis by simple 
multiplication of the probabilities a-Jh and a^/h taken separately. 

(37) If 

For ju^apa - l Jl =Pi/h W?i A - Ps/PiPz? 1 - - - by repeated 
applications of X. 

6. TAe Inverse Principle : 

(38) ^ = ^ - ^ provided W, a,*, and a* are 

each consistent. 

For aj/6A . l/h = 

and ^2/J/^ . 6/A = b/a 2 h . a^/t by X., 

whence the result follows, since b/h*Q, unless bh, is in- 


(38.1) If ajh^pv a<Jh=p 2 , 6/^A-^, l/a 2 h = q 2 , and 
+ ^2/6/1 = 1, then it easily follows that 



PiSi +J 
(38.2) If a-Jh^a^jh the above reduces to 


since aJJi^Q, unless aji is inconsistent. 

The proposition is easily extended to the cases in which the 
number of a's is greater than two. 

It will be worth while to translate this theorem into familiar 
language. Let 6 represent the occurrence of an event B, % 
and a 2 the hypotheses of the existence of two possible causes 
A x and A 2 of B, and Hi the general data of the problem. Then p x 
and p% are the a priori probabilities of the existence of A x and Ag 
respectively, when it is not known whether or not the event B 
has occurred ; q and j a the probabilities that each of the causes 
A! and Ag, if it exists, will be followed by the event B. Then 

- and - are the probabilities of the existence 

of A! and A 2 respectively after the event, i.e. when, in addition 
to our other data, we know that the event B has occurred. The 
initial condition, that bh must not be inconsistent, simply ensures 
that the problem is a possible one, i.e. that the occurrence of the 
event B is on the initial data at least possible. 

The reason why this theorem has generally been known as 
the Inverse Principle of Probability is obvious. The causal 
problems to which the Calculus of Probability has been applied 
are naturally divided into two classes the direct in which, given 
the cause, we deduce the effect ; the indirect or inverse in which, 
given the effect, we investigate the cause. The Inverse Principle 
has been usually employed to deal with the latter class of 

7. Theorems on the Combination of Premisses : 

The Multiplication Theorems given above deal with the com- 

bination of conclusions ; given a/h^ and a/h% we considered the 

relation of a^a^/h to these probabilities. In this paragraph the 

corresponding problem of the combination of premisses will be 


treated ; given a/h^ and a/h 2 we stall -consider the relation of 
to these probabilities. 

(39) alhjiji = 7 \ ~ 7 = 7 7 * _ 7 7 ~-7T by X. and (24.2) 

v ' 'I* ^ 7i-'^ n/i .n.-/h J-n.7t.-b~lh. J x ' 


where w is the a priori probability of the conclusion a and both 
hypotheses ^ and 4 2 jointly, and v is the d priori probability 
of the contradictory of the conclusion and both hypotheses ^ 
and A 2 jointly. 

(40) a/hit - 

. q + h^/dh 2 - (1 - gr)' 
h^ah^ . p 

^ . (1 - p) ' 
where ^ = a/A x and g = /7t 2 . 

.i) if ,-j, ^ 

7 ^ 2 

i -^i 

and increases with -~ 


These results are not very valuable and show the need of an 
original method of reduction. This is supplied by Sir. W. E. 
Johnson's Cumulative Formula, which is at present unpublished 
but which I have his permission to print below. 1 

8. It is first of all necessary to introduce a new symbol. Let 
us write 

XV. a/lh = {a n 1)}a/h Def. 
We may call {a*6} the coefficient of influence of b upon a on 
hypothesis h. 

XVI. . {al l l} {a&c\ = (a ll l) 1l c} Def. 
and similarly {a h b} {a&cdty = \aWcd! 1 e}. 

These coefficients thus belong by definition to a general class of 
operators, which we may call separative factors. 

(41) db/h = {a ll l} . a/h . l/h, 

since al/h = ajlh . 6/4. 

1 The substance of propositions (41) to (49) below is derived in its entirety 
from his notes, the exposition only is mine. 


Thus we may also call {a 7i &} the coefficient of dependence between 
a and 6 on hypothesis A. 

(4:1-1) abc/h = -fflW'c} . a/h . b/h . c/h. 

For abc/h = ]ab h c\ab/h . c/h by (41), 

= {ab n c} . {ab} . a/h . b/h . c/h by (41). 
(41.2) And in general 

abed ...fh = {a h b n c ll d h . . . } . a/h . b/h . c/h . d/h . . . 

(42) {a n b} = {b 7l a} 3 
since a/bh . b/h = b/ah . a/h. 

since afh . b/h . c/h = afh . c/h . b/h. 

(42.2) And in general we have a commutative rule, by which 
the order of the terms may be always commuted 
e.g. {a jL bc h defty = (Jc*aV def} 

{a h bc h def ll g} = {a n cb 7l fed h g} . 

(43) As a multiplier the separative factor operates so as to 
separate the terms that may be associated (or joined)' in the 

Thus [a&cd^e] . {a h b} = {aWcd^e}, 

for abcde/h = {ab u cd 1} e\ . ab/h . cd/h . e/h 

= \ab h cd ll e} . {a 1l b} . a/h . b/h . ci/A . /ft, 
and also abcde/h = {a h b h cd h e} . a/h . &//*, . c^/7z- . e/A. 
Similarly (for example) 

{dbc h d h ef} . {ab h c} . {a h b} = {a h b h c h d h ef} . 

/ A ji \ f h't.') f 7 \ f Ji 7\ 

For ab/h = {ab} ab/h . 

By a symbolic convention, therefore, we may put {ab} =1. 

(44.1) If {a*&}=l, it follows that a/A and 6/A are in- 
dependent arguments ; and conversely. 

(45) Rule of Eepetition {aa^fy = {a h b}. 

For oaft/A =a&/7i by (vi.) and (12). 

(46) The Cumulative Formula : 
x/ah : x'/ah : x"/ah : . . . 

= x/h . a/xh : x'/h . a/x f h : x"/h . a/x"h : . . . by (38). 
Take n + 1 propositions a, &, c . . . Then by repetition 
x/ah . x/bh . x/ch . . . : x'/a . x'b/ . x'fc . . . : #"/ . x"/b . x"/c ...:... 
- (x/h) n+l a/xh . b/xh ...: (x'/h) n+l afx'h . b/x f h . . . 

which may be written 


n +l n+l n-j-i 

Use/ah : Tin' I ah : Ux ff /ah : . . . 

71 + 1 714-1 

= (x/h.) n+I Ua/xh : (x'/h) n+l Ua/x f h :... 
%/kabe . . . : x'fhabc . . .: x"/habc . . . 

=x/h . (aSc . . .) fxh : x'/h . (aU . . .) /x'h : ... by (38), 


abc . . . /xh = {a x V l c . . . }Ua/xh by (41.2), 
.-. (xlh) n .z/habc . . . : (sG r /h) n .x f /Imbc . . . 

= {a* A y*c . . . }x/ah . x/bh . x/ch . . . : {a 

. x'fch ...:... 
which may be written 

(x/h) n . s?//ia&c . . . ac{a ! ' !> V 1l c . . . } . a?/A . x/bk . xjcli . . . 
where variations of x are involved. 

The cumulative formula is to be applied when, having accumu- 
lated the evidence a, b, c . . ., we desire to know the comparative 
probabilities of the various possible inferences x, x r . . . which 
may be drawn, and already know determinately the force of 
each of the items a, b, c . . . separately as evidence for x, x r . . . . 

Besides the factors x/ah, xjbh, etc., we require to know two 
other sets of values, viz. : (1) x/h, etc., i.e. the a priori 
probabilities of x, etc., and (2) {a xh b xlL c . . . }, etc., i.e. the 
coefficients of dependence between a, b 3 and c ... on hypotheses 
xh, etc. It may be remarked that the values {r/, il/ 'Z/ l7t c . . .}, 
{af'V^c ...}-... are not in any way related, even when x r =x. 

What corresponds to the cumulative formula has been em- 
ployed, sometimes, by mathematicians in a simplified form 
which is, except under special conditions, incorrect. First, it 
has been tacitly assumed that {a^b^e ...}, {a^b^'c ...}.., 
are all unity : so that 

(x/h) n x/habc . . . oc %/ah . x/bh . x/ch . . . 
Secondly, the factor (xjh) n has been omitted, so that 
x/habc . . . oc x/dh . x/bh . x/ch . . . 

It is this second incorrect statement of the formula which 
leads to the fallacious rule for the combination of the testimonies 
of independent witnesses ordinarily given in the text-books. 1 

(46.1). If ale... /xh = {a xh b xh c 1 . . } a/xh . b/xh . c/xh . . . 
then x/kabc . . . ^[a yll l\ . . . } xfah . x/bh . x/ch . . . 

1 See p 180 below. 


This result is exceedingly interesting. Mr. Johnson is the first to 
arrive at the simple relation, expressed above, between the direct 
and the inverse formulae : viz. that the same coefficient is re- 
quired for correcting the simple formulae of multiplication in 
both cases. As he remarks, however, while the direct formula 
gives the required probability directly by multiplication, the 
inverse formula gives only the comparative probability. 

(46.2) If x, x', x" . . . are exclusive and exhaustive alterna- 

_ v 



since x/halc . . . oc (xlh)~ ll {a cli l xjL G . . . }Ux/ah, 

and Sx'fhdbc ... =1 by (24.7). 

. o& f hale . . . a/h . l/h . c/h ... abc . . . Jx'/i 

x/h ale . . ./h aJxJi . l/xh . c/xh . . . 

[~x[ah xflh ~| 
' 1^ "ifh " J 
For ale . . . x/k = x/h . ale . . . /xh, 

ale . . . x/h ale . . . /xh a/h . l/h . c/h . . . 
ale . . . jh . x/k ale . . . /h ale . . . /h 

ale . . . /xh VajxJi l/xh ~| 

a/xh . l/xh . cjxh ... [_ a/h l/h J' 

, ^ i. ^ ^at , 

whence the result, since 7= -~-~, etc. 

a/A x/h 

(47.1) The above formula may be written in the condensed 

{sc,fh} n xfkabc ...^ {d*V*<t* . . .} efah.a/bh .xjch... 
." {</ k 'b ill <f h ..} ' xfaJt, .x/bh .x/ch...' 

This follows at once from (46.2), since x and x are exclusive and 
exhaustive alternatives. (It is assumed that xk, xh, and ah, 
etc., are not inconsistent.) 


This formula gives xfhabc ... in terms of x/ah, x/bh, etc., 
together with the three values x/h, {tf*fr t V A . . . ) and 


(4A i\ . . . _ &/hbcd . . . _ [a xh bcd . . . } . x/ah x/h 

xfhabcd ..." x/hbcd . . . {cf h lcd . . . } . x/ah ' x/h' 
This gives the effect on the odds (prob. x : prob. x) of the extra 
knowledge a. 

(49) When several data co-operate as evidence in favour of a 
proposition, they continually strengthen their own mutual 
probabilities, on the assumption that when the proposition 
is known to be true or to be false the data jointly are not 

I.e. if {a xh b xh c . . . } and {a^b m c . . . } are not less than 
unity, and x/Jch>x/h where Jc is any of the data a, 6, c . . ., then 
{a h b 7l c h d . . .} beginning with unity, continually increases, as 
the number of its terms is increased. 

ale . . . jh=xalc . . . jh+xabc . . ./h by (24.2). 

xfh . ale . . . [xh+x/h . abc . . . /xh. 
>%/h . TiafxJi . tyxh . . . +x/IiTla/xJi . l/Sh . . . 
(since {c? K Vh . . .} and {a* h V 7l c . . .} are not less than unity), 


xjh xfh J ' I x/h x/h 

abc.../h n ^x/ah x/bx "I -/7 

' ' rrr n uT - ^ xh ' U \ ^ --- ~n ---- +* h 
U[a/h . bjh . . .] L %/h x/h J 

^ rs/ah x/bh "1 
L x/h xjh J 

We can show that each additional piece of evidence a, 6, c ... 
increases the value of this expression. For let x/h . G +x/h . G' be 
its value when all the evidence up to k exclusive is taken, so that 

' x/Jch.G+x/kh.G' 

is its value when k is taken. Now G>Gr' since x/ah>x/h, etc., 
and x/ah<x/h, etc., by the hypothesis that the evidence 
favours x; and for the same reason x/kh-x/h, which is equal 
to x/h -x/kh, is positive. 

/. G (x/kh - x/h)>G'(x/h - x/kh), 
i.e. x/kh . G + x/kh . G'xe/A .Gr + x/h. G', 

the result. 


(49.1) The above proposition can be generalised for the 
case of exclusive alternatives x, x', x" . . . (in place of z, x). 
For {flW . . . } 
= xfh . 

from which it follows that, if {a xh b xh c . . }etc. <fl, and if 
{dAe}-l, {& 7t a;-l}, {c ft B-l}, etc., have the same sign, then 
{a ll V l c . . . } is increasing (with the number of letters) from unity. 
Mr. Johnson describes this result as a generalisation of 
the corrected " middle term fallacy" (see Chap. V. 4). 



THE use of the symbol for impossibility and 1 for certainty was 
first introduced by Leibnitz in a very early pamphlet, entitled 
Specimen certitudinis seu demonstrationum in jure, exhibitum in 
doctrina conditionum, published in 1665 (vide Coutiirat, Logique de 
Leibnitz, p. 553). Leibnitz represented intermediate degrees of 
probability by the sign J, meaning, however, by this symbol a 
variable between and 1. 

Several modern writers have made some attempt at a symbolic 
treatment of Probability. But with the exception of Boole, whose 
methods I have discussed in detail in Chapters XV., XVI., and 
XVII., no one has worked out anything very elaborate. 

Mr. McColl published a number of brief notes on Probability of 
considerable interest see especially his Symbolic Logic, Sixth Paper 
on the Calculus of Equivalent Statements, and On the Growth and Use 
of a Symbolical Language. The conception of probability as a relation 
between propositions underlies his symbolism, as it does mine. 1 The 

probability of a, relative to the a priori premiss h, he writes - ; and 
the probability, given b in addition to the a priori premiss, he writes 

~. Thus ~ = a/h, and % = afbh. The difference - -, i.e. the change 
b e e 

in the probability of a brought about by the addition of b to the 
evidence, he calls c the dependence of the statement a upon the state- 

1 I did not come across these notes until my own method was considerably 
developed. Mr. McColl has been the first to use the fundamental symbol of 


ment b,' and denotes it by &-. Thus 87 =0, where, in my termin- 
ology, b is irrelevant to a on evidence Ji. The multiplication and 

ob a, b b a 

addition formulae he gives as follows : = -.-=-.- 
e a e b 

a + b_a b ab 

' e * 

AT & A.& , A a 

Also 8- = s 8-, where A= - . 

o B a c 

It is surprising how little use he succeeds in making of these good 
results. He arrives, however, at the inverse formula in the shape 

c r v 
e r c r 

v r = n c r v 

i . 

where c x . . . c n are a series of mutually exclusive causes of the event 
v and include all possible causes of it ; reaching it as a generalisation 
of the proposition 

a b 

a e a 

b a b a b 
e a e a, 

In a paper entitled " Operations in Relative Number with Appli- 
cations to the Theory of Probabilities," - 1 Mr. B. I. Gilman attempted 
a symbolic treatment based on a frequency theory similar to Venn's, 
but made more precise and more consistent with itself : " Probability 
has to do, not with individual events, but with classes of events ; and 
not with one class, but with a pair of classes, the one containing, 
the other contained. The latter being the one with which we are 
principally concerned, we speak, by an ellipsis, of its probability 
without mentioning the containing class ; but in reality probability 
is a ratio, and to define it we must have both correlates given." But 
Mr. Oilman's symbolic treatment leads to very little. More recently 
R. Laemmel, in his Untersuchungen uber die Ermittlung von Wahr- 
scheirilicJikeiten, made a beginning on somewhat similar lines ; but 
in his case also the symbolic treatment leads to no substantial results. 

Apart from the writers mentioned above, there are a few who 
have incidentally made use of a probability symbol. It will be 
sufficient to cite Czuber. 3 He denotes the probability of an event 

1 Published in the volume of Johns Hopkins Studies in Logic. 
* Wahrscheinlichkeiterechnung, vol. i. pp. 43-48. 


E by W(E), and the probability of the event E given the occurrence of 
an event F by W F (E). He uses this symbol to give W F (E) = Wp(E) 

as the criterion of the independence of the events E and F (F denoting 
the non- occurrence of F) ; W F (E) = 1, as the expression of the fact 
that E is a necessary consequence of F ; and one or two other similar 

Finally there is in the Bulletin of the Physico-mathematical Society 
of Kazan for 1887 a memoir in Russian by Platon S. Porctzki entitled 
" A Solution of the General Problem of the Theory of Probability by 
Means of Mathematical Logic." I have seen it stated that Schroder 
intended to publish ultimately a symbolic treatment of Probability. 
Whether he had prepared any manuscript on the subject before his 
death I do not know. 



1. THE possibility of numerical measurement, mentioned at 
the close of Chapter III., arises out of the Addition Theorem 
(24.1). In introducing the definitions and the axiom, which are 
required in order to make the convention of numerical measure- 
ment operative, we may appear, as in the case of the original 
definitions of Addition and Multiplication, to be arguing in an 
artificial way. This appearance is due, here as in Chapter XII., 
to our having given the names of addition and multiplication to 
certain processes of compounding probabilities in advance of 
postulating that the processes in question have the properties 
commonly associated with these names. As common sense is 
hasty to impute the properties as soon as it hears the names, it 
may overlook the necessity of formally introducing them. 

2. The definitions and the axiom which are needed in order 
to give a meaning to numerical measurement are the following : 

XVII. a/h + {a/h + [a/h + (a/h + ...r terms)]} = r . a/h. Def . 

XVIII. If r . a/h = Iff, then a/h = - . l/f. Def. 


XIX. If b/f=q.c/g, then -.&//=?<>/#. Def. 

Thus if bjh a/h + a/h + ... to r terms, then the probability 
b/h is said to be r times the probability ajh ; hence if ab/h =0 and 
a/h = b/h, the probability (a + b)Jh is twice the probability a/h. 
If a and b are exhaustive as well as exclusive alternatives re- 
latively to h. so that (a+b)/h = l, since we take the relation of 
certainty as our unit, then a/h=b/h=%. 

We also need the following axiom postulating the existence of 
relations of probability corresponding to all proper fractions : 



(vii.) If q and r are any finite integers and q<r, there exists 
'a relation of probability which can be expressed, by means of the 

convention of the foregoing definitions, as - 


3. From these axioms and definitions combined with those 
of Chapter XII., it is easy to show (certainty being represented 
by unity and impossibility by zero) that we can manipulate 
according to the ordinary laws of arithmetic the " numbers " 
which by means of a special convention we have thus introduced 
to represent probabilities. Of the kind of proofs necessary 
for the complete demonstration of this the following is given as 
an example : 

(50) If a//=- and &//&=-, *//+&/& =^^1^. 

m n . mn 

Let the probabilitv =P, which exists by (vii.), 

" mn 

then n . P - - = a/f by (XIX.), 

and m . P = - = &//&, 


.-. a/f + b/h = n . P + m . P, if this probability exists, 

= P +P . . . to n terms +P + P . . . to m terms, 
=P +P . . . to m + n terms, 

by (XIX.). 


This probability exists in virtue of (vii.). 

4. Many probabilities in fact all those which are equal to 
the probability of some other argument which has the same 
premiss and of which the conclusion is incompatible with that 
of the original argument are numerically measurable in the 
sense that there is some other probability with which they are 
comparable in the manner described above. But they are not 
numerically measurable in the most usual sense, unless the pro- 
bability with which they are thus comparable is the relation 
of certainty. The conditions under which a probability a/h is 

numerically measurable and equal to - are easily seen. It 


is necessary that there should exist probabilities 
a y /7z, Q . . . a r /h r , such that 

= . . . = ajh q = . . . = a r \k 


i l>9 and 2^/7^ 1. 

i ' i 

If a/A-^ and 6/A- ^, it follows from (32) that ab/h^ 

only if a/h and b/Ji are independent arguments. Unless, there- 
fore, we are dealing with independent arguments, we cannot 
apply detailed mathematical reasoning even when the individual 
probabilities are numerically measurable. The greater part of 
mathematical probability, therefore, is concerned with arguments 
which are both independent and numerically measurable. 

5. It is evident that the cases in which exact numerical 
measurement is possible are a very limited class, generally 
dependent on evidence which warrants a judgment of equi- 
probability by an application of the Principle of Indifference. 
The fuller the evidence upon which we rely, the less likely is it to 
be perfectly symmetrical in its bearing on the various alternatives, 
and the more likely is it to contain some piece of relevant informa- 
tion favouring one of them. In actual reasoning, therefore, 
perfectly equal probabilities, and hence exact numerical measures, 
will occur comparatively seldom, 

The sphere of inexact numerical comparison is not, however, 
quite so limited. Many probabilities, which are incapable of 
numerical measurement, can be placed nevertheless between 
numerical limits. And by taking particular non-numerical 
probabilities as standards a great number of comparisons or 
approximate measurements become possible. If we can place 
a probability in an order of magnitude with some standard prob- 
ability, we can obtain its approximate measure by comparison. 

This method is frequently adopted in common discourse. 
When we ask how probable something is, we often put our ques- 
tion in the form Is it more or less probable than so and so ? 
where c so and so ' is some comparable and better known prob- 
ability. We may thus obtain information in cases where it would 
be impossible to ascribe any number to the probability in question. 
Darwin was giving a numerical limit to a non-numerical prob- 


ability when he said of a conversation with LyeU that he thought 
it no more likely that he should be right in nearly all points than 
that he should toss up a penny and get heads twenty times 
running. 1 Similar cases and others also, where the probability 
which is taken as the standard of comparison is itself non- 
numerical and not, as in Darwin's instance, a numerical one, 
will readily occur to the reader. 

A specially important case of approximate comparison is that 
of * practical certainty.' This differs from logical certainty since 
its contradictory is not impossible, but we are in practice com- 
pletely satisfied with any probability which approaches such 
a limit. The phrase has naturally not been used with complete 
precision ; but in its most useful sense it is essentially non- 
numerical we cannot measure practical certainty in terms of 
logical certainty. We can only explain how great practical 
certainty is by giving instances. We may say, for instance, that 
it is measured by the probability of the sun's rising to-morrow. 
The type which we shall be most likely to take will be that of a 
well- verified induction. 

6. Most of such comparisons must be based on the principles 
of Chapter V. It is possible, however, to develop a systematic 
method of approximation which may be occasionally useful. 
The theorems given below are chiefly suggested by some work 
of Boole's. His theorems were introduced for a different pur- 
pose, and he does not seem to have realised this interesting 
application of them ; but analytically his problem is identical 
with that of approximation. 2 This method of approximation 
is also substantially the same analytically as that dealt with by 
Mr. Yule under the heading of Consistence. 3 

1 Life and Letters, vol. ii. p. 240. 

3 In. Boole's Calculus we are apt to be left with an equation of the second 
or of an even higher degree from which to derive the probability of the conclu- 
sion ; and Boole introduced these methods in order to determine which of the 
several roots of his equation should be taken as giving the true solution of the 
problem in probability. In each case he shows that that root must be chosen 
which lies between certain limits, and that only one root satisfies this condition. 
The general theory to be applied in such cases is expounded by him in Chapter 
XIX. of The Laws of TTumght, which is entitled " On Statistical Conditions." 
But the solution given in that chapter is awkward and unsatisfactory, and he 
subsequently published a much better method in the Philosophical Magazine 
for 1864 (4th series, vol. viii.) under the title "On the Conditions by which the 
Solutions of Questions in. the Theory of Probabilities are limited." 

3 Theory of Statistics, chap. ii. 



(51) xy/h always lies between 1 x/h and x/h+y[h-l and 
between y/h and x/h+y/h - 1. 

For xy/h = x/h - xy/h by (24.2), 

= xfh - y/h . x/yh by X. 

Now x/yh lies between and 1 by (2) and (3), 

.-. xy/h lies between x/h and xjh -y/h, 

i.e. between x/h and x/h +y/h - 1. 

As xy/h<Q, the above limits may be replaced by xjh and 0, if 

We thus have limits for xy/h, close enough sometimes to be 
useful, which are available whether or not x/h and y/h are inde- 
pendent arguments. For instance, if y/h is nearly certain, xy/h 
=*x/h nearly, quite independently of whether or not x and y are 
independent. This is obvious ; but it is useful to have a simple 
and general formula for all such cases. 


(52) x^x 2 . . . x n+ i[h is always greater than 2 x r /h-n. 

For by (51) x^ . . . iv^/h >% 2 . . . xjh+x^/h - 1 

>XjXi . . . x n _ j/& + x jk + x tt+l /h - 2, 
and so on. 

(53) xy/h+xy/h is always less than x/h-y/h + 1, and less 
than y/h~x/h + l. 

For as in (51) ##/A = x/h - xy/h 

and xy/h = y/& - #y//i, 

/. xy/h + sjf/A = x/h - 2//7i/ + 1 - %xyfh, 
whence the required result. 

(54) xy/h - xy/h = a/^ + y/h - 1 . 

This proposition, wliich follows immediately from the above, 
is really out of place here. But its close connection with con- 
clusions (51) and (53) is obvious. It is slightly unexpected, 
perhaps, that the difference of the probabilities that both of two 
events will occur and that neither of them will, is independent of 
whether or not the events themselves are independent. 

7. It is not worth while to work out more of these results here. 
Some less systematic approximations of the same kind are given 
in the course of the solutions in Chapter XVII. 

In seeking to compare the degree of one probability with that* 
of another we may desire to get rid of one of the terms, on account 

1 In this and the following theorems the term ' between ' includes the 


of its not being comparable with any of our standard probabilities. 
Thus our object in general is to eliminate a given symbol of 
quantity from a set of equations or inequations. If, for instance, 
we are to obtain numerical limits within which our probability 
must lie, we must eliminate from the result those probabilities 
which are non-numerical. This is the general problem for 

(55) A general method of solving these problems when we 
can throw our equations into a linear shape so far as all symbols 
of probability are concerned, is best shown in the following 
example : 

Suppose we have X + v = a (i.) 

S (ii.) 

c (iiL) 

d (iv.) 

\ + p + <r + r = e (v.) 

l (vi.) 

where X, JJL, v, p, a, r, v represent probabilities which are to be 
eliminated, and limits are to be found for c in terms of the 
standard probabilities a, I, d, e, and 1. 

A,, //,, etc., must all lie between and 1. 

From (i.) and (iii.) cr =c -a ; from (ii.) and (iii.) v =c -b. 

From (i.), (ii.), and (iii.) \ = a + b-c : 
whence c-c&^O, e-6>0, a+b-c^Q, 

substituting for <r, -v, \ in (iv.), (v,), and (vi.) 

whence p = d -a - 
.: d-a-^ 
We have still to eliminate /A. ^d - a, 

/. d-a^c + d + e-a-b-I and e-fec+d + e-a -6-1. 
Hence we have : 

Upper limits of c: b + l-e,a + l~d,a + b (whichever is least); 

Lower limits of c : a, b (whichever is greatest). 

This example, which is only slightly modified from one given 
by Boole, represents the actual conditions of a well-known 
problem in probability* 



1. IN Definition XIII. of Chapter XII. a meaning was given, to 
the statement that a-Jh and a^/h are independent arguments. 
In Theorem (33) of Chapter XIV. it was shown that, if ajh and 
a%/h are independent, a- L a 2 fh^a l /h . a%fh. Thus where on given 
evidence there is independence between % and & 2 , the probability 
on this evidence of a^a^ jointly is the product of the probabilities 
of a^ and a z separately. It is difficult to apply mathematical 
reasoning to the Calculus of Probabilities unless this condition 
is fulfilled ; and the fulfilment of the condition has often been 
assumed too lightly. A good many of the most misleading 
fallacies in the theory of Probability have been due to a use of 
the Multiplication Theorem in its simplified form in cases where 
this is illegitimate. 

2. These fallacies have been partly due to the absence of 
a clear understanding as to what is meant by Independence. 
Students of Probability have thought of the independence of 
events, rather than of the independence of arguments or pro- 
positions. The one phraseology is, perhaps, as legitimate as the 
other ; but when we speak of the dependence of events, we are 
led to believe that the question is one of direct causal dependence, 
two events being dependent if the occurrence of one is a part 
cause or a possible part cause of the occurrence of the other. In 
this sense the result of tossing a coin is dependent on the existence 
of bias in the coin or in the method of tossing it, but it is inde- 
pendent of the actual results of other tosses ; immunity from 
smallpox is dependent on vaccination, but is independent of 
statistical returns relating to immunity ; while the testimonies 
of two witnesses about the same occurrence are independent, 
so long as there is no collusion between them. 



This sense, which it is not easy to define quite precisely, is 
at any rate not the sense with which we are concerned when we 
deal with independent probabilities. We are concerned, not with 
direct causation of the kind described above, but with * depend- 
ence for knowledge/ with the question whether the 'knowledge of 
one fact or event affords any rational ground for expecting the 
existence of the other. The dependence for knowledge of two 
events usually arises, no doubt, out of causal connection, or what 
we term such, of some kind. But two events are not independent 
for knowledge merely because there is an absence of direct causal 
connection between them ; nor, on the other hand, are they 
necessarily dependent because there is in fact a causal train which 
brings them into an indirect connection. The question is whether 
there is any known probable connection, direct or indirect. A 
knowledge of the results of other tossings of a coin may be hardly 
less relevant than a knowledge of the bias of the coin ; for a 
knowledge of these results may be a ground for a probable know- 
ledge of the bias. There is a similar connection between the 
statistics of immunity from smallpox and the causal relations 
between vaccination and smallpox. The truthful testimonies 
of two witnesses about the same occurrence have a common 
cause, namely the occurrence, however independent (in the legal 
sense of the absence of collusion) the witnesses may be. For the 
purposes of probability two facts are only independent if the 
existence of one is no indication of anything which might be a 
part cause of the other. 

3. "While dependence and independence may be thus con- 
nected with the conception of causality, it is not convenient to 
found our definition of independence upon this connection. A 
partial or possible cause involves ideas which are still obscure, and 
I have preferred to define independence by reference to the con- 
ception of relevance, which has been already discussed. Whether 
there really are material external causal laws, how far causal 
connection is distinct from logical connection, and other such 
questions, are profoundly associated with the ultimate problems 
of logic and probability and with many of the topics, especially 
those of Part III., of this treatise. But I have nothing useful to 
say about them. Nearly everything with which I deal can be 
expressed in terms of logical relevance. And the relations be- 
tween logical relevance and material cause must be left doubtful. 


4, It will be useful to give a few examples out of writers who, 
as I conceive, have been led into mistakes through misappre- 
hending the significance of Independence. 

Cournot, 1 in his work on Probability, which after a long period 
of neglect has come into high favour with a modern school of 
thought in France, distinguishes between e subjective probability ' 
based on ignorance and ' objective probability ' based on the 
calculation of ' objective possibilities/ an objective possibility ' 
being a chance event brought about by the combination or con- 
vergence of phenomena belonging to independent series. The 
existence of objectively chance events depends on his doctrine 
that, as there are series of phenomena causally dependent, so 
there are others between the causal developments of which there 
is independence. These objective possibilities of Cournot's, 
whether they be real or fantastic, can have, however, small 
importance for the theory of probability. For it is not known 
to us what series of phenomena are thus independent. If we had 
to wait until we knew phenomena to be independent in this sense 
before we could use the simplified multiplication theorem, most 
mathematical applications of probability would remain hypo- 

5. Cournot's c objective probability/ depending wholly on 
objective fact, bears some resemblances to the conception in the 
minds of those who adopt the frequency theory of probability. 
The proper definition of independence on this theory has been 
given most clearly by Mr. Yule 2 as follows : 

" Two attributes A and B are usually defined to be inde- 
pendent, within any given field of observation or ' universe/ 
when the chance of finding them together is the product of the 
chances of finding either of them separately. The physical 
meaning of the definition seems rather clearer in a different 
form of statement, viz. if we define A and B to be independent 
when the proportion of A's amongst the IPs of the given universe is 
the same as in that universe at large. If, for instance, the question 
were put, c What is the test for independence of smallpox attack 
and vaccination ? ' the natural reply would be, * The percentage 
of vaccinated amongst the attacked should be the same as in 
the general population.' . , ." 

1 For some account of Cournot, see Chapter XXIV. 3. 

2 " Notes on the Theory of Association of Attributes in Statistics," Bio- 
metrika, vol. iu p. 125. 


This definition is consistent with the rest of the theory 
to which it belongs, but is, at the same time., open to the 
general objections to it. 1 Mr. Yule admits that A and B may be 
independent in the world at large but not in the world of C's. 
The question therefore arises as to what world given evidence 
specifies, and whether any step forward is possible when, as is 
generally the case, we do not know for certain what the propor- 
tions in a given world actually are. As in the case of Cournot's 
independent series, it is in general impossible that we should 
know whether A and B are or are not independent in this sense. 
The logical independence for knowledge which justifies our 
reasoning in a certain way must be something different from 
either of these objective forms of independence. 

6. I come now to Boole's treatment of this subject. The 
central error in his system of probability arises out of his giving 
two inconsistent definitions of ' independence.' 2 He first wins 
the reader's acquiescence by giving a perfectly correct defini- 
tion : " Two events are said to be independent when the 
probability of the happening of either of them is unaffected by 
our expectation of the occurrence or failure of the other." 3 But 
a moment later he interprets the term in quite a different sense ; 
for, according to Boole's second definition, we must regard the 
events as independent unless we are told either that they must 
concur or that they cannot concur. That is to say, they are in- 
dependent unless we know for certain that there is, in fact, an 
invariable connection between them. " The simple events, x, y, z, 
will be said to be conditioned when they are not free to occur in 
every possible combination; in other words, when some com- 
pound event depending upon them is precluded from occurring. 

1 See Chapter VIII. 

2 Boole's mistake was pointed, out, accurately though, somewhat obscurely, 
by H. Wilbraham in his review "On the Theory of Chances developed in Professor 
Boole's Laws of Thought" (Phil. Mag. 4th series, vol. viL, 1854). Boole 
failed to understand the point of Wilbraham's criticism, and replied hotly, 
challenging him to impugn any individual results (" Reply to some Observations 
published by Mr. Wilbraham," Phil Mag. 4th series, voL viii., 1854). He 
returned to the same question in a paper entitled " On a General Method in 
the Theory of Probabilities," Phil. Mag. 4th series, voL viii., 1854, where he 
endeavours to support his theory by an appeal to the Principle of Indifference. 
McColl, in his "Sixth Paper on Calculus of Equivalent Statements," saw 
that Boole's fallacy turned on his definition of Independence; but I do 
not think he understood, at least he does not explain, where precisely Boole's 
mistake lay. 

3 Laws of Thought, p. 255, The italics in this quotation are mine. 


. . . Simple unconditioned events are by definition independent." x 
In fact as long as xz is possible, x and z are independent. This is 
plainly inconsistent with Boole's first definition, with which he 
makes no attempt to reconcile it. The consequences of his em- 
ploying the term independence in a double sense are far-reaching. 
For he uses a method of reduction which is only valid when the 
arguments to which it is applied are independent in the first 
sense, and assumes that it is valid if they are independent in the 
second sense. While his theorems are true if all the propositions 
or events involved are independent in the first sense, they are not 
true, as he supposes them to be, if the events are independent 
only in the second sense. In some cases this mistake involves 
hirn in results so paradoxical that they might have led "him 
to detect his fundamental error. 2 Boole was almost certainly 
led into this error through supposing that the data of a 
problem can be of the form, " Prob. x=p" i.e. that it is 
sufficient to state that the probability of a proposition is such 
and such, without stating to what premisses this probability is 
referred. 3 

It is interesting that De Morgan should have given, 
incidentally, a definition of independence almost identical 
with Boole's second definition : " Two events are independent 
if the latter might have existed without the former, or the 

* Op. dt. p. 258. 

2 There is an excellent instance of this, Laws of Thought, p. 286. Boole 
discusses the problem : Given the probability p of the disjunction e either Y 
is true, or X and Y are false,' required the probability of the conditional pro- 
position, * If X is true, Y is true.' The two propositions are formally equivalent ; 

but Boole, through the error pointed out above, arrives at the result 5? , 


where c is the probability of * If either Y is true, or X and Y false, X is true.' 
His explanation of the paradox amounts to an assertion that, so long as two 
propositions, which are formally equivalent when true, are only probable, they 
are not necessarily equivalent. 

3 In studying and criticising Boole's work on Probability, it is very im- 
portant to take into account the various articles which he contributed to the 
Philosophical Magazine during 1854, in which the methods of The Laws of 
Thought are considerably improved and modified. His last and most considered 
contribution to Probability is his paper ** On the application of the Theory of 
Probabilities to the question of the combination of testimonies or judgments," 
to be found in the JEdin. Phil. Trans, vol. xxi., 1857. This memoir contains a 
simplification and general summary of the method originally proposed in The 
Laws of Thought, and should be regarded as superseding the exposition of that 
book. In spite of the error already alluded to, which vitiates many of hia 
conclusions, the memoir is as full as are his other writings of genius and 


former without the latter, for anything that we know to the 
contrary." 1 

7. In many other cases errors have arisen, not through a 
misapprehension of the meaning of independence, but merely 
through careless assumptions of it, or through enunciating the 
Theorem of Multiplication without its qualifying condition. 
Mathematicians have been too eager to assume the legitimacy 
of those complicated processes of multiplying probabilities., for 
which the greater part of the mathematics of probability is 
engaged in supplying simplifications and approximate solutions. 
Even De Morgan was careless enough in one of his writings 2 
to enunciate the Multiplication Theorem in the following form : 
" The probability of the happening of two, three, or more events 
is the product of the probabilities of their happening separately 
(p. 398). . . . Knowing the probability of a compound event, 
and that of one of its components, we find the probability 
of the other by dividing the first by the second. This is a 
mathematical result of the last too obvious to require further 
proof (p. 401). 51 

An excellent and classic instance of the danger of wrongful 
assumptions of independence is given by the problem of deter- 
mining the probability of throwing heads twice in two consecutive 
tosses of a coin. The plain man generally assumes without 
hesitation that the chance is (J) 2 . For the d priori chance of 
heads at the first toss is J, and we might naturally suppose that 
the two events are independent, since the mere fact of heads 
having appeared once can have no influence on the next toss. 
But this is not the case unless we know for certain that the coin 
is free from bias. If we do not know whether there is bias, or 
which way the bias lies, then it is reasonable to put the probability 
somewhat higher than () 2 . The fact of heads having appeared 
at the first toss is not the cause of heads appearing at the second 
also, but the knowledge, that the coin has fallen heads already, 
affects our forecast of its falling thus in the future, since heads in 
the past may have been due to a cause which will favour heads 
in the future. The possibility of bias in a coin, it may be noticed, - 

1 " Essay on Probabilities " in the Cabinet Encyclopaedia, p. 26. De Morgan 
is not very consistent -with himself in his various distinct treatises on this 
subject, and other definitions may be found elsewhere. Boole's second defini- 
tion of Independence is also adopted by Macfarlane, Algebra of Logic, p. 21. 

2 " Theory of Probabilities " in the Encyclopaedia Metropolitana. 


always favours runs ' ; this possibility increases the probability 
both of c runs ' of heads and of ' runs ' of tails. 

This point is discussed at some length in Chapter XXIX. and 
further examples will be given there. In this chapter, therefore, 
I will do more than refer to an investigation by Laplace and to 
one real and one supposed fallacy of Independence of a type with 
which we shall not be concerned in Chapter XXTX. 

8. Laplace, in so far as he took account at all of the considera- 
tions explained in 7, discussed them under the heading of Des 
inegalites inconnues gui peuvent exister entre les chances que Fon 
suppose egales?- In the case, that is to say, of the coin with 
unknown bias, he held that the true probability of heads even 
at the first toss differed from J by an amount unknown. But 
this is not the correct way of looking at the matter. In the 
supposed circumstances the initial chances for heads and tails 
respectively at the first toss really are equal. What is not true 
is that the initial probability of ' heads twice * is equal to the 
probability of * heads once ' squared. 

Let us write c heads at first toss ' = A a ; * heads at second toss ' 
= & a . Then h 1 /h = h 2 fh = % 3 and hji^h = Ji^jhji . hjh. Hence 
hji^/h = {^i/A} 2 only if hJhJi^Ji^k, i.e. if the knowledge that 
heads has fallen at the first toss does not affect in the least the 
probability of its falling at the second. In general, it is true that 
Ji^TiJi will not differ greatly from h^/h (for relative to most hypo- 
theses heads at the first toss will not much influence our expectation 
of heads at the second), and J will, therefore, give a good approxi- 
mation to the required probability. Laplace suggests an ingeni- 
ous method by which the divergence may be diminished. If we 
throw two coins and define * heads ' at any toss as the face thrown 
by the second coin, he discusses the probability of heads twice 
running' with the first coin. The solution of this problem 
involves, of course, particular assumptions, but they are of a kind 
more likely to be realised in practice than the complete absence 
of bias. As Laplace does not state them, and as his proof is 
incomplete, it may be worth while to give a proof in detail. 

Let Sj, tfr ^2, t 2 denote heads and tails respectively with 
the first and second coins respectively at the first toss, and 
V %'> V t-2 the corresponding events at the second toss, then 

1 Esaai philosophise, p. 49. See also " M^moire sur les Probability" Him. 
de VAcad. p. 228, and op. D'Alembert, "Sur le calcul des probabilites," 
Opuscules matMmatiques (1780), vol. vii. 


the probability (with the above convention) of ' heads twice run- 
ning/ i.e. agreement between the two coins twice running, is 

Since 7& 2 VMA' + *A' A ) = WAVi' + *i*i'* *) ^7 tlie Principle 
of Indifference, and 
.-. (A 4- z 

Similarly ( VV + ^V)/ A = Zhji^/h . 

We may assume that hjh^'h^hjjh, i.e. that heads with one 
coin is irrelevant to the probability of heads with the other : and 
=J by the Principle of Indifference, so that 

since, (AjV + V/) being irrelevant to 

Now A 2 /(^2 / 3 ^1^1' + ^A': ^) ^ greater than J, since the fact of 
the coins having agreed once may be some reason for supposing 
they will agree again. But it is less than Ji^/h-Ji : for we may 
assume that h^/^, hji^ +t I t I ' ) Ti) is less than h%/(h% 9 hik^', A), 
and also that Ti^(h^ J^h^ 9 J^^h^hji^ i.e. that heads twice 
running with one coin does not increase the probability of heads 
twice running with a different coin. Laplace's method of tossing, 
therefore, yields with these assumptions, more or less legitimate 
according to the content of h, a probability nearer to J than is 
hjkjh. If V(V iW+i'> A ) = 2> tte]1 tlie probability is 
exactly J. 

9. Two other examples will complete this rather discursive 
commentary. It has been supposed that by the Principle of 
Indifference the probability of the existence of iron upon Sirius 
is J, and that similarly, the probability of the existence there of 
any other element is also J. The probability, therefore, that 
not one of the 68 terrestrial elements will be found on Sirius 
is (J) 68 , and that at least one will be found there is 1 -(J) 58 or 
approximately certain. This argument, or a similar one, has 
been seriously advanced. It would seem to prove also, amongst 


many other things, that at least one college exactly resembling 
some college at either Oxford or Cambridge will almost certainly 
be found on Sirius. The fallacy is partly due. as has been pointed 
out by Von Kries and others, to an illegitimate use of the Principle 
of Indifference. The probability of iron on Sirius is not ^. But 
the result is also due to the fallacy of false independence. 
It is assumed that the known existence of 67 terrestrial 
elements on Sirius would not increase the probability of the 
sixty-eighth's being found there also, and that their known 
absence would not decrease the sixty-eighth's probability. 1 

10. The other example is that of Maxwell's classic mistake in 
the theory of gases. 2 According to this theory molecules of gas 
move with great velocity in every direction. Both the directions 
and velocities are unknown, but the probability that a molecule 
has a given velocity is a function of that velocity and is inde- 
pendent of the direction. The maximum velocity and the mean 
velocity vary with the temperature. Maxwell seeks to 
determine, on these conditions alone, the probability that a 
molecule has a given velocity. His argument is ,as follows : 

If <f>(x) represents the probability that the component of 
velocity parallel to the axis of X is a;, the probability that the 
velocity has components x, y, z parallel to the three axes is 
<f>(x)<f>(y)<f)(z)- Thus if F(v) represents the probability of a total 
velocity v, we have <(#)<(2/)<(2) = F(v), where v 2 = x 2 +y z +z 2 . 
It is not difficult to deduce from this (assuming that the 

1 See Von Kries, Die Principien der WahrscJieinUMeiterechnung, p. 10. 
Stumpf (&ber den Begriffder mathem. WahrscheinlicJikeit, pp. 71-74) argues that 
the fallacy results from not taking into account the fact that there might be as 

many metals as atomic weights, and that therefore the chance of iron is -, where 

z is the number of possible atomic weights. A. Nitsche ( Vierteljsch. f. wissensck. 
PAt705., 1892) thinks that the real alternatives are 0, or only 1, or only 2 ... or 
68 terrestrial elements on Sirius, and that these are equally probable, the chance 

of each being g^. 

2 I take the statement of this from Bertrand's Calcul des probability, p. 30. 
Let me here quote a precocious passage on Probability regarded as a branch of 
Logic, from a letter written by Maxwell in his nineteenth year (1850), before 
he came up to Cambridge : " They say that Understanding ought to work 
by the rules of right reason. These rules are, or ought to be, contained in 
Logic ; but the actual science of logic is conversant at present only with things 
either certain, impossible, or entirely doubtful, none of which (fortunately) 
we have to reason on. Therefore the true logic for this world is the calcnlus 
of Probabilities, which takes account of the magnitude of the probability 
which is, or ought to be, in a reasonable man's mind" (Life, page 143). 


functions are analytical) that <$>(x) must be of the form 

It is generally agreed at the present time that this result is 
erroneous. But the nature of the error is, I think, quite different 
from what it is commonly supposed to be. 

Bertrand, 1 Poincare, 2 and Von Kries, 3 all cite this argument of 
Maxwell's as an illustration of the fallacy of Independence ; and 
argue that <j>(x) 9 <f>(y) 9 and <f>(z) cannot, as he assumes, represent 
independent probabilities, if, as he also assumes, the probabflity 
of a velocity is a function of that velocity. But it is not in this 
way that the error in the result really arises. If we do not know 
what function of the velocity the probability of that velocity is, 
a knowledge of the velocity parallel to the axes of x and y tells 
us nothing about the velocity parallel to the axis of 2. Maxwell 
was, I think, quite right to hold that a mere assumption that the 
probability of a velocity is some function of that velocity, does 
not interfere with the mutual independence of statements as to 
the velocity parallel to each of the three axes. Let us denote 
the proposition, ' the velocity parallel to the axis of X is x ' by 
X(#), the corresponding propositions relative to the axes of Y 
and Z by Y(^) and Z(z) s and the proposition e the total 
velocity is v * by V(v) ; and let k represent our d priori data. 
Then if X(#)/A = <(#) it is a justifiable inference from the 
Principle of Indifference that Y(2/)/A=<j6(^) and Z(z)/h=<f>(z). 
Maxwell infers from this that X(#)Y(^)Z(2)/&=<(a?)((y)<f>(z). 
That is to say, he assumes that Y(y)/X(#) . &*=Y(y)A an( i 
that Z(z)fY(y) . X(s) . h=Z(z)/h. I do not agree with the 
authorities cited above that this is illegitimate. So long as 
we do not know what function of the total velocity the prob- 
ability of that velocity is, a knowledge of the velocities parallel 
to the axes of x and y has no bearing on the probability of a given 
velocity parallel to the axis of z. But Maxwell goes on to infer 
that X(a5)Y(t/)Z(z)/&=V(v)/A, where v 2 =o? 2 4-y 2 + z 2 . It is here, 
and in a very elementary way, that the error creeps in. The 
propositions X(o?)Y(j/)Z(^) and V(i?) are not equivalent. The 
latter follows from the former, but the former does not follow 
from the latter. There is more than one set of values x, y, z, 

1 Calcul des probability, p. 30. 

2 Calcul des probabilites (2nd ed.), pp. 41-44, 

3 WahrscTwinlichlceitsrechnung, p. 199^ 


which will yield the same value v. Thus the probability V(^)/ 
is much greater than the probability X(x)Y(y)Z(z)/h. As we do 
not know the direction of the total velocity v, there are many 
ways, not inconsistent with our data, of resolving it into com- 
ponents parallel to the axes. Indeed I think it is a legitimate 
extension of the preceding argument to put V(v)/h=<j>(v) ; for 
there is no reason for thinking differently about the direction 
V from what we think about the direction X. 

A difficulty analogous to this occurs in discussing the problem 
of the dispersion of bullets over a target a subject round which, 
on account of a curiosity which it seems to have raised in the 
minds of many students of probability, a literature has grown up 
of a bulk disproportionate to its importance. 

11. I now pass to the Principle of Inverse Probability, a 
theorem of great importance in the history of the subject. With 
various arguments which have been based upon it I shall deal 
in Chapter innr. But it will be convenient to discuss here the 
history of the Principle itself and of attempts at proving it. 

It first makes its appearance somewhat late in the history of 
the subject. Not until 1763, when Bayes's theorem was com- 
municated to the Royal Society, 1 was a rule for the determination 
of inverse probabilities explicitly enunciated. It is true that 
solutions to inductive problems requiring an implicit and more 
or less fallacious use of the inverse principle had already been 
propounded, notably by Daniel Bernoulli in his investigations 
into the statistical evidence in favour of inoculation. 2 But the 
appearance of Bayes's Memoir marks the beginning of a new 
stage of development. It was followed in 1767 by a contribution 
from Michell 3 to the Philosophical Transactions on the distribu- 

1 Published in the Phil Trans, vol. Hit, 1763, pp. 376-398. This Memoir 
was communicated by Price after Bayes's death ; there was a second Memoir 
in the following year (vol. liv. pp. 298-310), to which Price himself made some 
contributions. See Todhunter's History, pp. 299 et seq. Thomas Bayes was 
a dissenting minister of Tunbridge Wells, who was a Fellow of the Boyal Society 
from 1741 until his death in 1761. A German edition of his contributions to 
Probability has been edited by Timerding. 

2 " Essai d'une nouvelle analyse de la mortality causee par la petite verole, 
et des avantages de rinoculation pour la prevenir," Hist, de VAcad., Paris, 1760 
(published 1766). Bernoulli argued that the recorded results of inoculation 
rendered it a probable cause of immunity. This is an inverse argument, though 
Bayes's theorem is not used in the course of it. See also D. Bernoulli's Memoir 
on the Inclinations of the Planetary Orbits. 

3 MichelTs argument owes more, perhaps, to Daniel Bernoulli than to 


tion of tlie stars, to which further reference will be made in 
Chapter XXV. And in 1774 the rule was clearly, though not 
quite accurately, enunciated by Laplace in his "Memoire sur 
la probabilite des causes par les evenemens " (Memoires 
presenter a V Academic des Sciences, vol. vi., 1774). He states 
the principle as follows (p. 623) : 

" Si Tin evenement pent etre produit par nn nombre n de 
causes diflerentes, les probabilites de 1'existence de ces causes 
prises de Tevfenement sont entre elles comme les probabilites de 
1'evenement prises de ces causes ; et la probabilite de Texistence 
de chacune d' elles est egale a la probabilite de 1'evenement prise 
de cette cause, divisee par la somme de toutes les probabilites 
de Fevenement prises de chacune de ces causes." 

He speaks as if he intended to prove this principle, but he only 
give explanations and instances without proof. The principle is 
not strictly true in the form in which he enunciates it, as will be 
seen on reference to theorems (38) of Chapter XIV. ; and the 
omission of the necessary qualification has led to a number of 
fallacious arguments, some of which will be considered in Chapter 

12. The value and originality of Bayes's Memoir are con- 
siderable, and Laplace's method probably owes much more to 
it than is generally recognised or than was acknowledged by 
Laplace. The principle, often called by Bayes's name, does not 
appear in his Memoir in the shape given it by Laplace and 
usually adopted since ; but Bayes's enunciation is strictly correct 
and his method of arriving at it shows its true logical connection 
with more fundamental principles, whereas Laplace's enuncia- 
tion gives it the appearance of a new principle specially introduced 
for the solution of causal problems. The following passage 1 
gives, in my opinion, a right method of approaching the 
problem : " If there be two subsequent events, the probability 

of the second =j= and the probability of both together , and, it 

being first discovered that the second event has happened, from 

hence I guess that the first event has also happened, the prob- 

ability I am in the right is -." If tide occurrence of the first event 


1 Quoted by Todhunter, op. cit. p. 296. Todhunter underrates the import- 
ance of this passage, which he finds unoriginal, yet obscure. 


PT. n 

is denoted by a and of the second by b, this corresponds to 

ab/h =a/bh . b/h and therefore a/bh ^-L- ; for abjh =~ s b/h =- 9 

b/fi .N Jf 

a/bh = . The direct and indeed fundamental dependence of the 


inverse principle on the rule for compound probabilities was not 
appreciated by Laplace. 

13. A number of proofs of the theorem have been attempted 
since Laplace's time, but most of them are not very satisfactory, 
and are generally couched in such a form that they do no more 
than recommend the plausibility of their thesis. Mr. McColl 1 gave 
a symbolic proof, closely resembling theorem (38) when differ- 
ences of symbolism are allowed for ; and a very similar proof 
has also been given by A. A. Markoff. 2 I am not acquainted with 
any other rigorous discussion of it. 

Von Kries 3 presents the most interesting and careful example 
of a type of proof which has been put forward in one shape or 
another by a number of writers. We have initially, according to 
this view, a certain number of hypothetical possibilities, all 
equally probable, some favourable and some unfavourable to our 
conclusion. Experience, or rather knowledge that the event 
has happened, rules out a number of these alternatives, and we 
are left with a field of possibilities narrower than that with which 
we started. Only part of the original field or Spielraum of 
possibility is now admissible (zuldssig). Causes have d posteriori 
probabilities which are proportional to the extent of their occur- 
rence in the now restricted field of possibility. 

There is much in this which seems to be true, but it hardly 
amounts to a proof. The whole discussion is in reality an 
appeal to intuition. For how do we know that the possibilities 
admissible d posteriori are still, as they were assumed to be a 
priori, equal possibilities ? Von Kries himself notices that there 
is a difficulty ; and I do not see how he is to avoid it, except by 
the introduction of an axiom. 

This was in fact the course taken by Professor Donkin in 1851, 
in an article which aroused some interest in the Philosophical 

1 "Sixth Paper on the Calculus of Equivalent Statements," Proc. Lond. 
Math. Soc., 1897, voL xxviii. p. 567. See also p. 155 above. 

2 Wdhrscheinlich.Jceitsrechn'ung, p. 178. 

3 Die Principien d&r WahrscheinlichJceitsrechnuiig, pp. 117-121. The above 
account of Von Kries's argument is much condensed. 


Magazine at the time, but which, has since been forgotten. 
Donkin's theory is, however, of considerable interest. He laid 
down as one of the fundamental principles of probability the 
following : 1 

" If there be any number of mutually exclusive hypotheses 
hjijis ... of which the probabilities relative to a particular state 
of information are p^p^Pz . - ., and if new information be gained 
which changes the probabilities of some of them, suppose of 
h lll+l and all that follow, without having otherwise any reference 
to the rest, then the probabilities of these latter have the same 
ratios to one another, after the new information, that they had 
before." 2 

DonMn goes on to say that the most important case is where 
the new information consists in the knowledge that some of the 
hypotheses must be rejected, without any further information 
as to those of the original set which are retained. This is the 
proposition which Von Kries requires. 

As it stands, the phrase " without having otherwise any 
reference to the rest" obviously lacks precision. An interpreta- 
tion, however, can be put upon it, with which the principle is 
true. If, given the old information and the truth of one of the 
hypotheses h . . . h m to the exclusion of the rest, the probability 
of what is conveyed by the new information is the same whichever 
of the hypotheses h^ . . . h in has been taken, then DonkiVs 
principle is valid. For let a be the old information, a' the new, 
and let h r /a =p r , h r /aa' =p r ' ; then 

v ' v' 
.". = , etc., if a'/h r a=ta'/h s a, which is the condition already 

Pr Ps 


14. Difficulties connected with the Inverse Principle have 
arisen, however, not so much in attempts to prove the principle 
as in those to enunciate it though it may have been the lack 

1 " On certain Questions relating to the Theory of Probabilities," PhiL Mag. 
4th series, voL i., 1851. 

2 It is interesting to notice that an axiom, practically equivalent to this, 
has been laid down more lately by A. A. Markoff ( Wdhrscheinlich1ceitsrech,nung 9 
p. 8) under the title 6 Unabhangigkeitsaxiom.' 



of a rigorous proof that lias been responsible for the frequent 
enunciation of an inaccurate principle. 

It will be noticed that in the formula (38-2) the d priori 
probabilities of the hypotheses % and a z drop out if p =p 2i and 
the results can then be expressed in a much simpler shape. This 
is the shape in which the principle is enunciated by Laplace for 
the general case, 1 and represents the uninstructed view expressed 
with great clearness by De Morgan : 2 " Causes are likely or un- 
likely, just in the same proportion that it is likely or unlikely 
that observed events should follow from them. The most 
probable cause is that from which the observed event could most 
easily have arisen." If this were true the principle of Inverse 
Probability would certainly be a most powerful weapon of proof, 
even equal, perhaps, to the heavy burdens which have been laid 
on it. But the proof given in Chapter XIV. makes plain the 
necessity in general of taking into account the d priori prob- 
abilities of the possible causes. Apart from formal proof this 
necessity commends itself to careful reflection. If a cause is 
very improbable in itself, the occurrence of an event, which 
might very easily follow from it, is not necessarily, so long as 
there are other possible causes, strong evidence in its favour. 
Amongst the many writers who, forgetting the theoretic qualifica- 
tion, have been led into actual error, are philosophers as diverse 
as Laplace, De Morgan, Jevons, and Sigwart, Jevons 3 going 
so far as to maintain that the fallacious principle he enunciates 
is "that which common sense leads us to adopt almost in- 
stinctively.' 5 

15. The theory of the combination of premisses dealt with 
in 7, 8 of Chapter XIV. has not often been discussed, and the 
history of it is meagre. Archbishop Whately 4 was led astray 

1 See the passage quoted above, p. 175. 

* " Essay on Probabilities,'* in the Cabinet Encyclopaedia, p. 27. 

3 Principles of Sci ^nce f vol. i. p. 280. 

4 Logic, 8th ed. p. 211 : " As in the case of two probable premisses, the 
conclusion is not established except upon the supposition of their being both 
true, so in the case of two distinct and independent indications of the truth 
of some proposition, unless both of them fail, the proposition must be true : 
we therefore multiply together the fractions indicating the probability of the 
failure of each the chances against it and, the result being the total chances 
against the establishment of the conclusion by these arguments, this fraction 
being deducted from unity, the remainder gives the probability for it. E.g. a 
certain book is conjectured to be by such and such an author, partly, 1st, from 
its resemblance in style to his known works ; partly, 2nd, from its being attri- 


by a superficial error, and De Morgan, adopting the same mis- 
taken rule, pushed it to the point of absurdity. 1 Bishop Terrot 2 
approached the question more critically. Boole's 3 last and 
most considered contribution to the subject of probability dealt 
with the same topic. I know of no discussion of it during the 
past sixty years. 

Boole's treatment is full and detailed. He states the problem 
as follows : " Required the probability of an event z, when two 
circumstances x and y are known to be present, the probability 
of the event z, when we know only of the existence of the circum- 
stances x, being p, and the probability, when we only know of 
the existence of y, being j." 4 His solution, however, is vitiated 
by the fundamental error examined in 6 above. Two of his 
conclusions may be mentioned for their plausibility, but neither 
is valid. 

" If the causes in operation, or the testimonies borne/' he 

buted to him by some one likely to be pretty well informed. Let the probability 
of the conclusion, as deduced from one of these arguments by itself, be supposed 
J, and in the other case ^ ; then the opposite probabilities mil be % and f , which 
multiplied together give as the probability against the conclusion. ..." 

The Archbishop's error, in that a negative can always be turned into an 
affirmative by a change of verbal expression, was first pointed out by a mere 
diocesan, Bishop Terrot, in the Edin. Phil. Travis. voL xxi. The mistake is well 
explained by Boole in the same volume of the Edin. Phil. Trans. : " A confusion 
may here be noted between the probability that a conclusion is proved, and the 
probability in favour of a conclusion furnished by evidence which does not prove 
it. In the proof and statement of his rule, Archbishop Whately adopts the 
former view of the nature of the probabilities concerned in the data. La the 
exemplification of it, he adopts the latter." 

1 " Theory of Probabilities," Encyclopaedia Metropolitan, p. 400. He shows 
by means of it that "if any assertion appear neither likely nor unlikely in 
itself, then any logical argument in favour of it, however weak the premisses, 
makes it in some degree more likely than not a theorem which will be readily 
admitted on its own evidence." He then gives an example : " a priori 
vegetation on the planets is neither likely nor unlikely ; suppose argument 
from analogy makes it %- ; then the total probability is -f . ^ or f ." De 
Morgan seems to accept without hesitation the conclusion to be derived from 
this, that everything which is not impossible is as probable as not. 

8 " On the Possibility of combining two- or more Probabilities of the same 
Event, so as to form one definite Probability," Edin. Phil. Trans., 1856, voL Tm. 

3 " On the Application of the Theory of Probabilities to the Question of the 
Combination of Testimonies or Judgments," Edin. PhiL Trans., 1857, voL xxi. 

4 Loc. cit. p. 631. Boole's principle (Zoc. cit. p. 620) that " the mean strength 
of any probabilities of an event which are founded upon different judgments 
or observations is to be measured by that supposed probability of the event 
a priori which those judgments or observations following thereupon would not 
tend to alter," is not correct if it means more than that the mean strength of 
z/x and zjy is to be measured by zjxy. 


argues, " are, separately, such as to leave the mind in a state of 
equipoise as respects the event whose probability is sought, 
united they will but produce the same effect." If, that is to say, 
/&!=: J and a/# 2 = , he concludes that a/^ 2 =J. The plausi- 
bility of this is superficial. Consider, for example, the following 
instance : ^ = A is black and B is black or white, h 2 = B is black 
and A is black or white, a =both A and B are black. Boole also 
concluded without valid reason that afJiJi^ increases, the greater 
the a priori improbability of the combination hji^. 

16. The theory of " Testimony " itself, the theory, that is to 
say, of the combination of the evidence of witnesses, has occupied 
so considerable a space in the traditional treatment of Probability 
that it will be worth while to examine it briefly. It may, however, 
be safely said that the principal conclusions on the subject set 
out by Condorcet, Laplace, Poisson, Cournot, and Boole, are 
demonstrably false. The interest of the discussion is chiefly due 
to the memory of these distinguished failures. 

It seems to have been generally believed by these and other 
logicians and mathematicians 1 that the probability of two 
witnesses speaking the truth, who are independent in the sense 
that there is no collusion between them, is always the product 
of the probabilities that each of them separately will speak the 
truth. 2 On this basis conclusions such as the following, for 
example, are arrived at : 

X and Y are independent witnesses (i.e. there is no collusion 
between them). The probability that X will speak the truth is 
x, that Y will speak the truth is y. X and Y agree in a particular 
statement. The chance that this statement is true is 


For the chance that they both speak the truth is xy, and the 
chance that they both speak falsely is (1 -x)(I -y). As, in this 

1 Perhaps M. Bertrand should be registered as an honourable exception. 
At least he points out a precisely analogous fallacy in an example where two 
meteorologists prophesy the weather, Galcul des Probability p. 31. 

2 E.g., Boole, Laws of Thought, p. 279. 

De Morgan, Formal Logic, p. 195. 
Condorcet, JEssai, p. 4. 
Lacroix, Traiti, p. 248. 
Cournot, Exposition, p. 354. 
Poisson, JRecherches, p. 323. 
Tins list could be greatly extended. 


case, our hypothesis is that they agree, these two alternatives 
are exhaustive ; whence the above result, which may be found 
in almost every discussion of the subject. 

The fallacy of such reasoning is easily exposed by a more 
exact statement of the problem. For let a x stand for " X x asserts 
a," and let aja^Ji^x^ where h, our general data, is by itself 
irrelevant to a, i.e., x is the probability that a statement is true 
of which we only know that X x has asserted it. Similarly let us 
write 6/62^=^2, where 6 2 stands for " X 2 asserts 6." The above 
argument then assumes that, if X x and X 2 are witnesses who are 
causally independent in the sense there is no collusion between 
them direct or indirect, ab/a l b 2 h=a/a l 7i . b/b 2 h=x 1 x St . 

But a6/a 1 & 2 A = a/o 1 66 2 ^ . b/OjbJi, and this is not equal to XjX 2 
unless aja^bbji = a/a^Ti and b/a^b^Ji =bfbji. It is not a sufficient 
condition for this, as seems usually to be supposed, that X x and X 2 
should be witnesses causally independent of one another. It is 
also necessary that a and 6, i.e. the propositions asserted by the 
witnesses, should be irrelevant to one another and also each of 
them irrelevant to the fact of the assertion of the other by a 
witness. "If a knowledge of a affects the probability either of 
b or of b l9 it is evident that the formula breaks down. In the one 
extreme case, where the assertions of the two contradict one 
another, ab/a^b^h^O. In the other extreme, where the two agree 
in the same assertion, i.e. where a = 6, aja-pb^h = 1 and not = afaji. 

17. The special problem of the agreement of witnesses, who 
make the same statement, can be best attacked as follows, a 
certain amount of simplification being introduced. Let the 
general data h of the problem include the hypothesis that X x and 
X 2 are each asked and reply to a question to which there is only 
wie correct answer. Let a t = " X$ asserts a in reply to the ques- 
tion/' and m i = << X 4 gives the correct answer to the question." 

Then , , , , , 

m^jaji^x^ and m^a^n, =# 2> 

x and # 2 being, in the conventional language of thi- problem, 
the " credibilities " of the witnesses. We have, since the wit- 
nesses agree and since a follows from m^ and m^ follows from aa^ 

Also, since the witnesses are, in the ordinary sense, "independent " 


witnesses, aja^ah^a^ah and a^a^ah^a^ah ; that is to say, the 
probability of X 2 's asserting a is independent of the fact of Xj's 
having asserted a, given we know that a is, in fact, true or false, 
as the case may be. 

The probability that, if the witnesses agree, their assertion is 


a^ajaji + a^afaji a^a-^ah . x^ -f a^a^Sh . (1 - x z )' 
If this is to be equal to 1 -- -, we must have 

a^a^ah 1 - a; 2 " 

Now . 1 , 7 = - r_ T by the hypothesis of " independence " 
a^a^ah a 2 /ah J J r r 

aa z /h alh __a/aji a/h 

aa. z fh a/h dfaji afh 

x. 2 d/Ji 

l-x 2 a/h 

This then is the assumption which has tacitly slipped into the 
conventional formula, that a/A=a/A = J. It is assumed, that 
is to say, that any proposition taken at random is as likely as 
not to be true, so that any answer to a given question is, d priori, 
as likely as not to be correct. Thus the conventional formula 
ought to be employed only in those cases where the answer 
which the " independent '' witnesses agree in giving is, d priori 
and apart from their agreement, as likely as not. 

18. A somewhat similar confusion has led to the controversy 
as to whether and in what manner the d priori improbability 
of a statement modifies its credibility in the mouth of a witness 
whose degree of reliability is known. The fallacy of attaching 
the same weight to a testimony regardless of the character of 
what is asserted, is pointed out, of course, by Hume in the Essay 
on Miracles, and his argument, that the great d priori improb- 
ability of some assertions outweighs the force of testimony 
otherwise reliable, depends on the avoidance of it. The correct 
view is also taken by Laplace in his Essai phUosopTiigtce (pp. 


98-102), where lie argues that a witness is less to be believed 
when he asserts an extraordinary fact, declaring the opposite 
view (taken by Diderot in the article on " Certitude " in the 
Encyclopedic) to be inconceivable before " le simple bon sens." 

The manner in which the resultant probability is affected 
depends upon the precise meaning we attach to " degree of re- 
liability " or " coefficient of credibility." If a witness's credi- 
bility is represented by x s do we mean that, if a is the true answer, 
the probability of his giving it is x, or do we mean that if he 
answers a the probability of a's being true is x ? These two things 
are not equivalent. 

Let a x stand for " a is asserted by the witness " ; h^ for our 
evidence bearing on the witness's veracity ; and h 2 for other 
evidence bearing on the truth of a. Let ajfiji^ i.e. the d priori 
probability of a apart from our knowledge of the fact that the 
witness has asserted it, be represented by p. 

Let a/aj^x^ and a 1 faJi l =x 2 : l so that 0^ = -.% In 

general afTi^^a^/Ji^. Do we mean by the witness's credibility 
ccj or x 2 ? 

We require ajajiji^. 

Let o 1 /5^ 1 =7 < 3 i.e. the probability, apart from our special 
knowledge concerning a, that, if a is false, the witness will hit on 
that particular falsehood. 

+ a 

it . (1 -p) 

for aJahrJi^^a-Jah-L and a fl jdh i h 2 =a 1 /dh ly since, given certain 
knowledge concerning a, A 2 is irrelevant to the probability of a^ 
19. Generally speaking, all problems, in regard to the com- 
bination of testimonies or to the combination of evidence derived 
from testimony with evidence derived from other sources, may 
be treated as special instances of the general problem of the 
combination of arguments. Beyond pointing out the above 
plausible fallacies, there is little to add. Mr. W. K Johnson, 
however, has proposed a method of defining credibility, which 
is sometimes valuable, because it regards the witness's credibility 
not absolutely, but with reference to a given type of question, 


so that it enables us to measure the force of the witness's testimony 
under special circumstances. If a represents the fact of A's 
testimony regarding x, then we may define A's credibility for x 
as a, where a is given by the equation 

xjah =x/h + a<\/x/h . x/h ; 

so that a-\/x/h . x/h measures the amount by which A's assertion 
of x increases its probability. 

20. One of the most ancient problems in probability is con- 
cerned with the gradual diminution of the probability of a past 
event, as the length of the tradition increases by which it is 
established. Perhaps the most famous solution of it is that 
propounded by Craig in his Theologiae Christianae Principia 
MatJiematiea, published in 1699. 1 He proves that suspicions of 
any history vary in the duplicate ratio of the times taken from 
the beginning of the history in a manner which has been described 
as a kind of parody of Newton's Principia. " Craig," says 
Todhunter, " concluded that faith in the Gospel so far as it 
depended on oral tradition expired about the year 880, and that 
so far as it depended on written tradition it would expire in the 
year 3150. Peterson by adopting a different law of diminution 
concluded that faith would expire in 1789." 2 About the same 
time Locke raised the matter in chap. xvi. bk. iv. of the 
Essay Concerning Human Understanding : " Traditional testi- 
monies the farther removed, the less their proof. ... No 
Probability can rise higher than its first original." This is 
evidently intended to combat the view that the long acceptance 
by the human race of a reputed fact is an additional argument 

1 See Todhunter's History, p. 54. It has been suggested that the anonymous 
essay in the Phil Trans, for 1699 entitled " A Calculation of the Credibility 
of Human Testimony" is due to Craig. In this it is argued that, if the 
credibilities of a set of witnesses are p . . . p w then if they are 
successive the resulting probability is the product p^p 2 . . . p n ; if they are 
concurrent, it is : _ 

This last result follows from the supposition that the first witness leaves an 
amount of doubt represented by 1 p l ; of this the second removes the fraction 
p 2 , and so on. See also Lacroix, Traiti elementaire, p. 262. The above theory 
was actually adopted by BicquiUey. 

2 In the Budget of Paradoxes De Morgan quotes Lee, the Cambridge Orientalist, 
to the effect that Mahometan writers, in reply to the argument that the I^oran 
has not the evidence derived from Christian miracles, contend that, as evidence 
of Christian miracles is daily weaker* a time must at last arrive when it will 
fail of affording assurance that they were miracles at all : whence the necessity 
of another prophet and other miracles. 


in its favour and that a long tradition increases rather than 
diminishes the strength of an assertion. " This is certain," says 
Locke, " that what in one age was affirmed upon slight grounds, 
can never after come to be more valid in future ages, by being 
often repeated." In this connection he calls attention to " a 
rule observed in the law of England, which is, that though the 
attested copy of a record be good proof, yet the copy of a copy 
never so well attested, and by never so credible witnesses, will 
not be admitted as a proof in Judicature." If this is still a good 
rule of law, it seems to indicate an excessive subservience to the 
principle of the decay of evidence. 

But, although Locke affirms sound maxims, he gives no theory 
that can afford a basis for calculation. Craig, however, was the 
more typical professor of probability, and in attempting an 
algebraic formula he was the first of a considerable family. The 
last grand discussion of the problem took place in the columns 
of the Educational Times* Macfarlane 2 mentions that four 
different solutions have been put forward by mathematicians 
of the problem : " A says that B says that a certain event took 
place ; required the probability that the event did take place, 
Pi and p 2 being A's and B's respective probabilities of speaking 
the truth." Of these solutions only Cayley's is correct. 

1 Reprinted in Mathematics from the Educational Times, vol. zxvii. 

a Algebra of Logic, p. 151. Macfarlane attempts a solution of the general 
problem without success. Its solution is not difficult, if enough unknowns are 
introduced, but of very little interest. 



1. THE present chapter deals with ' problems ' that is to 
say, with applications to particular abstract questions of some of 
the fundamental theorems demonstrated in Chapter XIV. It 
is without philosophical interest and should probably be omitted 
by most readers. I introduce it here in order to show the ana- 
lytical power of the method developed above and its advantage 
in ease and especially in accuracy over other methods which 
have been employed. 1 2 is mainly based upon some problems 
discussed by Boole. 3-7 deal with the fundamental theory 
connecting averages and laws of error. 8-11 treat discursively 
the Arithmetic Average, the Method of Least Squares, and 

2. In the following paragraph solutions are given of some 
problems posed by Boole in chapter xx. of his Laws of Thought. 
Boole's own method of solving them is constantly erroneous, 2 
and the difficulty of his method is so great that I do not know 
of any one but himself who has ever attempted to use it. The 
term e cause * is frequently used in these examples where it might 
have been better to use the term c hypothesis.' For by a possible 
cause of an event no more is here meant than an antecedent 
occurrence, the knowledge of which is relevant to our anticipation 
of the event ; it does not mean an antecedent from which the 
event in question must follow. 

(56) The d priori probabilities of two causes A^ and A^ 
are c x and c 2 respectively. The probability that if the cause A x 

1 Such examples as these might sometimes be set to test the wits of students. 
The problems on Probability usually given are simply problems on mathematical 
combinations. These, on the other hand, are really problems in logic. 

2 For the reason given in 6 of Chapter XVI. The solutions of problems 
L VI., for example, in the Laws of Thought, chap. xx. s are all erroneous. 



occur, an event E will accompany it (whether as a consequence 
of A! or not), is p l9 and the probability that E will accompany A^, 
if Ag present itself, is p%. Moreover, the event E cannot appear 
in the absence of both the causes A x and Ag. Required the prob- 
ability of the event E. 

This problem is of great historical interest and has been called 
Boole's c Challenge Problem.' Boole originally proposed it for 
solution to mathematicians in 1851 in the Cambridge and Dublin 
Mathematical Journal. A result was given by Cayley 1 in the 
Philosophical Magazine, which Boole declared to be erroneous. 2 
He then entered the field with his own solution. 3 " Several 
attempts at its solution," he says, " have been forwarded to me, 
all of them by mathematicians of great eminence, all of them 
admitting of particular verification, yet differing from each other 
aod from the truth." 4 After calculations of considerable length 
and great difficulty he arrives at the conclusion that u is the 
probability of the event E where u is that root of the equation 

-ffg) - u] (u 

which is not less than c^p^ and c^p z and not greater than 
1 -^(1 -PJ, 1 -c 2 (l -y 2 ), or c^ + cfcpa- 

This solution can easily be seen to be wrong. For in the 
case where A x and A% cannot both occur, the solution is 
whereas Boole's equations do not reduce to 

1 Pkil. Mag. 4th series, vol. vi 

2 Cayley's solution was defended against Boole by Dedekind (Grell&'s Journal, 
voL 1. p. 268). The difference arises out of the extreme ambiguity as to the 
meaning of the terms as employed by Cayley. 

3 "Solution of a Question in the Theory of Probabilities," Phil Mag. 4th 
series, voL vii., 1854. This solution is the same as that printed by Boole 
shortly afterwards in the Laws of Thought, pp. 321-326. In the Phil. Mag. 
Wilbraham gave as the solution u ^c^+c^-z, where z is necessarily less 
than either c^ or 2 . This solution is correct so far as it goes, but is not 
complete. The problem is also discussed by Macfarlane, Algebra of Logic, 
p. 154. 

4 In proposing the problem Boole had said : * e The motives which have 
led me, after much consideration, to adopt, with reference to this question, a 
course unusual in the present day, and not upon slight grounds to be revived, 
are the following : First, I propose the question as a test of the sufficiency of 
received methods. Secondly, I anticipate that its discussion wiH in some 
measure add to our knowledge of an important branch of pure analysis." 
When printing his own solution in the Laws of Thought, he adds, that the 
above " led to some interesting private correspondence, but did not elicit a 
solution.' * 


this simplified form. The mistake which Boole has made is 
the one general to his system, referred to in Chapter XVL, 6. 1 

The correct solution, which is very simple, can be reached as 
follows : 

Let a l5 # 2 3 e assert the occurrences of the two causes and the 
event respectively, and let h be the data of the problem. 

Then we have ajh=c^ a^/h^c^ ^l^=Pu e/aji=p 2 : w e 
require ejh. Let e/h=u, and let c^ajeh^z. Since the event 
cannot occur in the absence of both the causes, 

It follows from this that d^eh^O, unless e/h^Q, 
i.e. (% + aj/eh = 1, 

whence a-Jeh 4- a 2 /eJi = 1 + a^ajeh by (24) . 

Now ajeh = ^ and a 2 M = ^, 



where z is the probability after the event that both the causes were 

If we write 

y = a^/ek . e/h = uz, 
so that u = (c l p I + c 2 ^ 2 ) ~ y - 

Boole's solution fails by attempting to be independent of 
y or 2. 

(56.1). Suppose that we wish to find limits for the solu- 
tion which are independent of y and z: then, since 


by (24.2) and (4). 

Similarly e/h^l~ c^+c^p^. From the same equations it appears 
that eh^c and 

1 Boole's error is pointed out and a correct solution given in Mr. McColTs 
"Sixth Article on the Calculus of Equivalent Statements" (Proc. Lond. Math. 
Soc. vol. xxviii. p. 562). 


/. u lies between 

Id* pa^i + ^2 

the greatest of \ L ^ 1 and the least of - 1 -Cifl -w-,) 

It will be seen that these numerical limits are the same as the 
limits obtained by Boole for the roots of his equations. 

(56.2) Suppose that the d priori probabilities of the causes Cj 
and c 2 are to be eliminated. The only limit we then have is 

(56.3) Suppose that one of the d priori probabilities c 2 is to be 
eliminated. We then have limits c^p^u^ 1 - ^ + c^. If, there- 
fore, C-L is large, u does not differ widely from c^p^. 

(56.4) Suppose p 2 is to be eliminated. We then have 

If therefore c^ is large or c 2 small, u does not differ widely 
from C^PI. 

(56.5) If a-Ja 2 h=a : Jh, i.e. if our knowledge of each of the 
causes is independent, we have a closer approximation. For 

y = ea^a^/Ji = e/a^a^h . a-Ja 2 h . a 
;. u = 

(57) We may now generalise (56) and discuss the case of n 
causes. If an event can only happen as a consequence of one 
or more of certain causes A l5 A 2 , . . . A tt , and if ^ is the d priori 
probability of the cause A x and p^ the probability that, if the 
cause A! be known to exist^ the event E will occur : required the 
probability of E. 

This is Boole's problem VI. (Laws of Thought, p. 336). As 
the result of ten pages of mathematics, he finds the solution to be 
the root lying between certain limits of an equation of the n th 
degree which he cannot solve. I know no other discussion of the 
problem. The solution is as follows : 

e/h = earjh + ea-Jh = ea^Jh + ejaji . a^Jh = eajj/i + c^ (i.) 
ed-Jh = ed^d^/k + ed-Ja z h . ajh = ed^d^h + c a . 

e/a z h - eajaji 


/. ejh = 

and e&iO&Jh = ea^d^a^h . c 

In general 

o . . . d r _ l lli = 

= ed 1 . . . d r /h + c r {e/a r k - 
= ed l ... d r /h + c r p r -ed I 


/. finally we have e/h-ed^. . . d n /h + c r jp, r - 

1 2 

But since the w causes are supposed to be exhaustive 


Let ea^. . . d r _ ^/h = 7i r ; 

TO Jl 

then ^/A = ^c r p r - Sw r .(iii.). 

1 2 

(57.1) If our knowledge of the several causes is independent, 
if , that is to say, our knowledge of the existence of any one of 
them is not relevant to the probability of the existence of any 
other, so that a r jaji = a r /h = e r , then 

ed 1 . . .d r ^a r = edi . . . d,._a r . c r 



Let e/di . . . d r _- L a r h m n 

rn r=n ss=r-l 

then o/A = 2 c^ r - 2 c r [l - II (1 - c s ) 

These results do not look very promising as they stand, but 
they lead to some useful approximations on the elimination of 
m r and n r and to some interesting special cases. 

H. xvn 



(57.2) From equation (i.) it follows that e/h>c I p l and 

<\(1 -ft) ; and from equation (ii.) that 
.-. e/h lies between 

the greatest of - | and the least of 1 - ' i(l -j 

(57.3) Further, if the causes are independent it follows from 
(57.1) that 

so that efh lies between 
the greatest of- 

and the 
least of 

(57.4) Now consider the case in which PI =p 2 = . . . =p n = 1, 
i.e. in which any of the causes would be sufficient, and in which 
the causes are independent. Then m r = 1 ; so that 

rn r=n 

-1 -(1- 

(57.5) Let CJL, c 2 . . . c n be small quantities so that their 
squares and products may be neglected. 

i.e. the smaller the probabilities of the causes the more do they 
approach the condition of being mutually exclusive. 1 

(57.6) The d posteriori probability of a particular cause a r 
after the event has been observed is 

^ M=f K^ 

6 I tlr 


(This is Boole's problem IX., p. 357). 
1 Boole arrives at this result, Laws of Thought, p. 346, but I doubt his proof. 


(58) The probability of the occurrence of a certain natural 
phenomenon under given circumstances is p. There is also a 
probability a of a permanent cause of the phenomenon, i.e. of a 
cause which would always produce the event under the circum- 
stances supposed. What is the probability that the phenomenon, 
being observed n times, will occur the n + 1* ? 

This is Boole's problem X. (Laws of Thought, p. 358). Boole 
arrives by his own method at the same result as that given below. 
It is necessary first of all to state the assumption somewhat 
more precisely. If x r asserts the occurrence of the event at the 
r tjl trial and t the existence of the c permanent cause ' we have 

x r /h =p, t/h = a, x r /th = 1 , 
and we require x n +i/Xi - * = y+i- 

It is also assumed that if there is no permanent cause the prob- 
ability of x s is not affected by the observations x r , etc., i.e. 

x s lx r . . . xfli = x s /th^ 
ntl ^_x i f/h_x s /h-x s t/h p-a 

jrr ---- 7 -- - - 

t/h t/h \-a 

r^tjh p-a x 1 . . . x r _ 1 /th . t/h 

a p-a\l -a 

i_-t _> 

a + p-a(- 

Also y\~P an -d y%- 


- .* assumption, which is tacitly introduced by Boole, is not generally 
justifiable. I use it here, as my main purpose is to illustrate a method. The 
same problem, without this assumption, will be discussed in dealing with Pure 


p _ a -i 

so that 

(58.1) If p=a, y n =~i. ; for if an event can only occur as the 
result of a permanent cause, a single occurrence makes future 
occurrences certain under similar conditions. 


(by easy algebra) ; 

and p is always >a and <1. 

So that Q; - a)f ^- - ) is positive and decreases as r increases, 

As ^ increases y n \ 6, where 

so that for any value of TJ however small a value of n can be 
found such that <?? so long as a is not zero. 

(58.3) t n the a posteriori probability of a permanent cause 
after n successful observations is 

x I ...x n /th.t/h_ a 

IflJj-t . . tL n fb j 

- e', where e /: 

- a,\ n 


So that t n approaches the limit unity as n increases, so long as a 
is not zero. 

3. The following is a common type of statistical problem. 1 
We are given a series of measurements, or observations, or 
estimates of the true value of a given quantity ; and we wish to 
determine what function of these measurements will yield us 
the most probable value of the quantity, on the basis of this evid- 
ence. The problem is not determinate unless we have some 
good ground for making an assumption as to how likely we are 
in each case to make errors of given magnitudes. But such an 
assumption, with or without justification, is frequently made. 

The functions of the original measurements which we com- 
monly employ, in order to yield us approximations to the most 
probable value of the quantity measured, are the various kinds 
of means or averages the arithmetic mean, for example, or 
the median. The relation, which we assume, between errors of 
different magnitudes and the probabilities that we have made 
errors of those magnitudes, is called a law of error. Corresponding 
to each law of error which we might assume, there is some function 
of the measurements which represents the most probable value 
of the quantity. The object of the following paragraphs is to 
discover what laws of error, if we assume them, correspond to 
each of the simple types of average, and to discover this by means 
of a systematic method. 

4. Let us assume that the real value of the quantity is either 
b l9 . . . b r . . . b n , and let a r represent the conclusion that the 
value is, in fact, b r . Further let x r represent the evidence that 
a measurement has been made of magnitude y r . 

If a measurement y p has been made, what is the probability 
that the real value is b s ? The application of the theorem of 
inverse probability yields the following result : 

, , xjaji- aJh 


^Xylaji. a r /h 


(the number of possible values of the quantity being n), where 
Ji stands for any other relevant evidence which we may have, 
in addition to the fact that a measurement x p has been made. 
Next, let us suppose that a number of measurements y^ . . . y m 

1 The substance of 3-7 has been printed in the Journal of the Royal 
Statistical Society, voL Ixxiv. p. 323 (February 1911), 


have been made ; what is now the probability that the real value 
is b f ? We require the value of ajxfo - - #A As before, 


At this point we must introduce the simplifying assumption 
that, if we knew the real value of the quantity, the different 
measurements of it would be independent, in the sense that a 
knowledge of what errors have actually been made in some of 
the measurements would not affect in any way our estimate of 
what errors are likely to be made in the others. "We assume, 
in fact, that x r fx p . . . x s a r h=x r /a j h. This assumption is ex- 
ceedingly important. It is tantamount to the assumption that 
our law of error is unchanged throughout the series of observations 
in question. The general evidence Ji 9 that is to say, which justifies 
our assumption of the particular law of error which we do assume, 
is of such a character that a knowledge of the actual errors made 
in a number of measurements, not more numerous than those 
in question, are absolutely or approximately irrelevant to the 
question of what form of law we ought to assume. The law 
of error which we assume will be based, presumably, on an 
experience of the relative frequency with which errors of different 
magnitudes have been made under analogous circumstances in 
the past. The above assumption will not be justified if the 
additional experience, which a knowledge of the errors in the new 
measurements would supply, is sufficiently comprehensive, rela- 
tively to our former experience, to be capable of modifying our 
assumption as to the shape of the law of error, or if it suggests 
that the circumstances, in which the measurements are being 
carried out, are not so closely analogous as was originally supposed. 

With this assumption, i.e. that a^, etc., are independent of 
one another relatively to evidence afo etc., it follows from the 
ordinary rule for the multiplication of independent probabilities 

that qm 


a s /h. 

q ^ m - = 

2 Uxjtkfi. a T /h 
"=iL<=i J 


The most probable value of the quantity under measurement, 
given the m measurements y l} etc. which is our quaesitum is 
therefore that value which makes the above expression a maxi- 
mum. Since the denominator is the same for all values of 6 SJ 
we must find the value which makes the numerator a maximum. 
Let us assume that a 1 /k=a z /h= . . . =&JA. We assume, that 
is to say, that we have no reason a, priori (i.e. before any measure- 
ments have been made) for thinking any one of the possible 
values of the quantity more likely than any other. We require, 


therefore, the value of 6,., which makes the expression Ilxjaji 

9 = 1 

a maximum. Let us denote this value by y. 

We can make no further progress without a further assump- 
tion. Let us assume that xjaji namely, the probability of a 
measurement y q assuming the real value to be b s is an algebraic 
function / of y q and b s , the same function for all values of y q and 
b s within the limits of the problem. 1 We assume, that is to say, 
xjajk. =f(y ti ,b s ), and we have to find the value of 6 S , namely y, 


which makes Hf(y q ,y) a maximum. Equating to zero the 


differential coefficient of this expression with respect to y, we 

have q 3?f'tevy) =Q* where /' = C This equation may be 
q-if(y q ,y) dy 

written for brevity in the form 2^ 3 = 0. 

If we solve this equation for y, the result gives us the value of 

the quantity under observation, which is most probable relatively 
to the measurements we have made. 

The act of differentiation assumes that the possible values of y 
are so numerous and so uniformly distributed within the range 
in question, that we may, without sensible error, regard them as 

5. This completes the prolegomena of the inquiry. We are 

1 Gauss, in obtaining the normal law of error, made, in effect, the more 
special assumption that x q /ajt is a function of e q only, where e q is the error and 
eg = b 8 -yq. We shall find in the sequel that all gym metrical laws of error, 
such that positive and negative errors of the same absolute magnitude are 
equally likely, satisfy this condition the normal law, for example, and the 
simplest median law. But other laws, such as those which lead to the geometric 
mean, do not satisfy it. 

2 Since none of the measurements actually made be impossible, none of 
the expressions f(yq,y) can vanish. 


now in a position to discover what laws of error correspond to 
given assumptions respecting the algebraic relation between the 
measurements and the most probable value of the quantity, and 
vice versa. For the law of error determines the form of f(y q ,y). 

f r 
And the form oif(y q ,y) determines the algebraic relation S^=0 

between the measurements and the most probable value. It 
may be well to repeat that f(y q ,y) denotes the probability to 
us that an observer will make a measurement y q in observing a 
quantity whose true value we know to be y. A law of error tells 
us what this probability is for all possible values of y q and y 
within the limits of the problem. 

(i.) If the most probable value of the quantity is equal to the 
arithmetic mean of the measurements, what law of error does this 
imply ? 

-f - , 

2^- (/ = must be equivalent to S(y-^ g )=0 ? since the 

most probable value y must equal 2y tf . 

.-. = <l>"(y)(y -y q ) where $"(y) is some function which 

is not zero and is independent of y q . 

-/&' (y}(y y^wy ~^~ ^(2/t/) where ilrfyaj is some : . 
tion independent of y. 

So that f q = 

Any law of error of this type, therefore, leads to the arithmetic 
mean of the measurements as the most probable value of the 
quantity measured. 

If we put <j>(y) = -k 2 y* and ty(y q ) = -A^ 2 +log A, we obtain 
/^Ae""* 2 ^"" 2 ^ 8 , the form normally assumed. 

=Ae~~ fca * ffS , where z q is the absolute magnitude of the error in 
the measurement y q . 

This is, clearly, only one amongst a number of possible solu- 
tions. But with one additional assumption we can prove that 
this is the only law of error which leads to the arithmetic mean. 


Let us assume tliat negative and positive errors of the same 
absolute amount are equally likely. 
In this case/, must be of the form 

Differentiating with respect to y, 

But $ n (y) is, by hypothesis, independent of y q . 

/. 8(y - y^f = -& 2 where k is constant ; integrating, 

% ~y q ? = -*% ~%) 2 + logC and we have/, =Ae~ fca( ^^ )2 (where 
A = BC). 

(ii.) What is the law of error, if the geometric mean of the 
measurements leads to the most probable value of the quantity 1 

1 q=*JH 

In this case 2^-^ = must be equivalent to TLy q =y m , i.e. to 




Proceeding as before, we find that the law of error is 

There is no solution of this which satisfies the condition that 
negative and positive errors of the same absolute magnitude are 
equally likely. For we must have 

which is impossible. 

The simplest law of error, which leads to the geometric mean, 
seems to be obtained by putting <j>'(y)= -ky, ^(^)=0. This 

=A ^ 

A law of error, which leads to the geometric mean of the 
observations as the most probable value of the quantity, has been 
previously discussed by Sir Donald McAlister (Proceedings of the 
Royal Society, vol. xxix. (1879) p. 365), His investigation de- 
pends upon the obvious fact that, if the geometric mean of the 


observations yields the most probable value of the quantity, the 
arithmetic mean of the logarithms of the observations must yield 
the most probable value of the logarithm of the quantity. Hence, 
if we suppose that the logarithms of the observations obey the 
normal law of error (which leads to their arithmetic mean as the 
most probable value of the logarithms of the quantity), we can 
by substitution find a law of error for the observations themselves 
which must lead to the geometric mean of them as the most 
probable value of the quantity itself. 

If, as before, the observations are denoted by y q , etc., and the 
quantity by y, let their logarithms be denoted by l q) etc., and by 
L Then, if I q9 etc., obey the normal law of error,/(Z g ,Z) = Ae~ /:a(Z *"~ Z)S . 
Hence the law of error for y q9 etc., is determined by 

and the most probable value of y must, clearly, be the geometric 
mean of y q , etc. 

This is the law of error which was arrived at by Sir Donald 
McAlister. It can easily be shown that it is a special case of the 
generalised form which I have given above of all laws of error 
leading to the geometric mean. For if we put ^r(y q ) = - & 2 (log y q )*, 
and <f>'(y) =2& 2 log y, we have 

f _ A fW log y log ^+/2fc 3 togj/ dy-WQos yd* 

Jq i 5 y J y 

log y log v q "~ 27t * (log y)3 + ** 

A similar result has been obtained by Professor J. C. Kapteyn. 1 
But he is investigating frequency curves, not laws of error, and 
this result is merely incidental to his main discussion. Has 
method, however, is not unlike a more generalised form of Sir 
Donald McAlister's. In order to discover the frequency curve 
of certain quantities y, he supposes that there are certain other 
quantities z 9 functions of the quantities y, which are given by 
z=F(^), and that the frequency curve of these quantities z is 
normal. By this device he is enabled in the investigation of a 
type of skew frequency curve, which is likely to be met with 
often, to utilise certain statistical constants corresponding to 

1 Skew Frequency Curves, p. 22, published by the Astronomical Laboratory 
at Groningen (1903). ' 


those which have been already calculated for the normal 

In fact the main advantage both of Sir Donald McAlister's 
law of error and of Professor Kapteyn's frequency curves lies in 
the possibility of adapting without much trouble to unsymmetrical 
phenomena numerous expressions which have been already 
calculated for the normal law of error and the normal curve of 
frequency. 1 

This method of proceeding from arithmetic to geometric laws 
of error is clearly capable of generalisation. We have dealt with 
the geometric law which can be derived from the normal arith- 
metic law. Similarly if we start from the simplest geometric 

law of error, namely, / 3 =A (- } e~ kZy , we can easily find, by 

\fc7Q 7 
writing logy = Z and Iogy q = l q , the corresponding arithmetic 

law, namely, /g-Ae^"^"*^, which is obtained from the 
generalised arithmetic law by putting <j>(l)=k*e l and 
And, in general, corresponding to the arithmetic law 


we have the geometric law 
f A^' l(ff 

J q 


y -log s, y a =log z q9 J ^^ dz = <(log z) and 
(iii.) "What law of error does the harmonic mean imply ? 
In this case, 2^=0 must be equivalent to 2j( --- ) =0. 

Proceeding as before, we find that / fl 
A simple form of this is obtained by putting <j>'(y) = - i* 2 ^ 2 and 

^)=-*V Then /, = A6^-^'=A6-^ With this law, 
positive and negative errors of the same absolute magnitude are 
not equally likely. 

(iv.) If the most probable value of the quantity is equal to the 
median of the measurements, what is the law of error ? 

The median is usually defined as the measurement which 

1 It may be added that Professor Kapteyn's monograph brings forwara 
considerations which would be extremely valuable in determining the typesof 
phenomena to which geometric laws of error are likely to be applicable, y 


occupies the middle position when the measurements are ranged 
in order of magnitude. If the number of measurements m is odd, 

the most probable value of the quantity is the - th, and, if the 


number is even, all values between the th and the ( + 1 jth are 

2 \ 2 / 

equally probable amongst themselves and more probable than 
any other. For the present purpose, however, it is necessary to 
make use of another property of the median, which was known 
to Fechner (who first introduced the median into use) but which 
seldom receives as much attention as it deserves. If y is the 
median of a number of magnitudes, tlie sum of the absolute differences 
(i.e. the difference always reckoned positive) between y and each of 
the magnitudes is a minimum. /The median y of y^ y z . . . y m is 


found, that is to say, by making %\y q -y\ a Tni'nrn where 

\y q -y\ is the difference always reckoned positive between y q 
and y. 

We can now return to the investigation of the law of error 

corresponding to the median. 

Write \y-y q \=^ Then since %z q is to be a minimum we 


y y 

must have &?~ - g =0. Whence, proceeding as before, we have 
i s 2 

/ =Ae/^*' Wy+ * (2/g) - 
The simplest case of this is obtained by putting 

whence f q 

This satisfies the additional condition that positive and nega- 
tive errors of equal magnitude are equally lik^r Thus ia this 
important respect the median is as satisfactory as the arithmetic 
mean, and the law of error which leads to it is as simple. It also 
resembles the normal law in that it is a function of the error only, 
and not of the magnitude of the measurement as well. 

The median law of error, f q = Ae~ fc *^, where z q is the absolute 
amount of the error always reckoned positive, is of some historical 


interest, because it was the earliest law of error to be formulated. 
The first attempt to bring the doctrine of averages into definite 
relation with the theory of probability and with laws of error was 
published by Laplace in 1774 in a memoir " sur la probability des 
causes par les evenemens." x This memoir was not subsequently 
incorporated in his Theorie analytigue, and does not represent his 
more mature view. In the Theorie he drops altogether the law 
tentatively adopted in the memoir, and lays down the main lines 
of investigation for the next hundred years by the introduction 
of the normal law of error. The popularity of the normal law, 
with the arithmetic mean and the method of least squares as its 
corollaries, has been very largely due to its overwhelming ad- 
vantages, in comparison with all other laws of error, for the pur- 
poses of mathematical development and manipulation. And in 
addition to these technical advantages, it is probably applicable 
as a first approximation to a larger and more manageable group 
of phenomena than any other single law. So powerful a hold 
indeed did the normal law obtain on the minds of statisticians, 
that until quite recent times only a few pioneers have seriously 
considered the possibility of preferring in certain circumstances 
other means to the arithmetic and other laws of error to the 
normal. Laplace's earlier memoir fell, therefore, out of remem- 
brance. But it remains interesting, if only for the fact that a 
law of error there makes its appearance for the first time. 

Laplace sets himself the problem in a somewhat simplified 
form : " Determiner le milieu que Ton doit prendre entre trois 
observations donnees d'un m&me ph&iomene." He begins by 
assuming a law of error z = <f>(y), where z is the probability of an 
error y ; and finally, by means of a number of somewhat arbitrary 

assumptions, arrives at the result </>(2) e~" ly . If this formula 


is to follow from his arguments, y must denote the absolute error, 
always taken positive. It is not unlikely that Laplace was led 
to this result by considerations other than those by which he 
attempts to justify it. 

Laplace, however, did not notice that his law of error led to 

the median. For, instead of firming the most probable value, 

which would have led him straight to it, he seeks the " mean of 

error " the value, that is to say, which the true value is as likely 

1 Memoires preaentes d FAcadimie des Sciences, vol. vi. 


to fall short of as to exceed. Tills value is, for the median law, 
laborious to find and awkward in the result. Laplace works it 
out correctly for the case where the observations are no more 
than ifiree. 

6. I do not think that it is possible to find by this method a 
law of error which leads to the mode. But the following general 
formulae are easily obtained : 

(v.) If ^0(y^y] =0 is the law of relation between the measure- 
ments and the most probable value of the quantity, then the law 
of error f,.(y q ,y) is given by f q ^A.e fe(y ^" ( ^^ M . Since f q lies 
between and l,fQ(y q y)$'\y)dy + 'fy(y^ + log A must be negative 
for all values of y q and y that are physically possible ; and, since 
the values of y q are between them exhaustive, 

where the summation is for all terms that can be formed by giving 
y q every value d priori possible. 

(vi.) The most general form of the law of error, when it is 
assumed that positive and negative errors of the same magnitude 
are equally probable, is Ae~ 7j * /(3/ ~^ a , where the most probable 
value of the quantity is given by the equation 

2/) 2 = o, whe f'(y -y/ - JT 

The arithmetic mean is a special case of this obtained by putting 
f(y-y fl )* = (y-yq)* > an( l ^e median is a special case obtained 

by putting f(y - y q f = + v% - y) 2 - 

We can obtain other special cases by putting 

when the law of error is Ae""^"^ 4 and the most probable values 
are the roots of my* - 3y 2 !% + 3y2y 2 a - %</ -0 ; and by putting 

/(y -%) 2 -log (S-y a ) 3 ,, when the law of error is _ 3j ,, and 

V" c/'jf' 

the most probable values the roots of 2 - =0. In all these 


cases the law is a function of the error only. 

7. These results may be summarised thus. We have 
assumed : 

(a) That we have no reason, before making measurements, for 


supposing that the quantity we measure is more likely to have 
any one of its possible values than any other. 

(6) That the errors are independent, in the sense that a 
knowledge of how great an error has been made in one case does 
not affect our expectation of the probable magnitude of the error 
in the next. 

(c) That the probability of a measurement of given magnitude, 
when in addition to the d priori evidence the real value of the 
quantity is supposed known, is an algebraic function of this 
given magnitude of the measurement and of the real value of the 

(d) That we may regard the series of possible values as con- 
tinuous, without sensible error. 

(e) That the d priori evidence permits us to assume a law of 
error of the type specified in (c) ; i.e. that the algebraic function 
referred to in (c) is known to us d priori. 

Subject to these assumptions, we have reached the following 
conclusions : 

(-1) The most general form of the law of error is 

leading to the equation 5 0(y q y) ^0, connecting the most probable 
value and the actual measurements, where y is the most probable 
value and y qi etc., the measurements. 

(2) Assuming that positive and negative errors of the same 
absolute magnitude are equally likely, the most general form is 
/^Ae-Wfc-** 1 , leading to the equation $(y-y q )f'(y-y q )* = Q, 

where f'z =fz. Of the special cases to which this form gives 

rise, the most interesting were 

(S^-Aa-^-^-Ae-**, where * q -\y-y q \, leading to 
the arithmetic mean of the measurements as the most probable 
value of the quantity ; and 

(4) f q =A.e- k ** q , leading to the median. 

(5) The most general form leading to the arithmetic mean is 
/ fl -A^<M*-*>-*&>+**>, with the special cases (3), and 

(6) /^Ae***^-^-***. 

(7) The most general form leading to the geometric mean is 

he special cases . 


'' N ** 

. - l ', and 

(10) The most general form leading to the harmonic mean is 
) , with the special case 

(12) The most general form leading to the median is 

with the special case (-4). 

In each of these expressions, f q is the probability of a measure- 
ment y q , given that the true value is y. 

8. The doctrine of Means and the allied theory of Least 
Squares comprise so extensive a subject-matter that they cannot 
be adequately treated except in a volume primarily devoted to 
them. As, however, they are one of the important practical 
applications of the theory of probability, I am unwiUing to pass 
them by entirely; and the following discursive observations, 
chiefly relating to the Normal Law of Error, will serve, taken in 
conjunction with the paragraphs immediately preceding, to 
illustrate the connection between the theories of this treatise 
and the general treatment of averages. 

9. The Claims of the Arithmetic Average. By definition the 
arithmetic average of a number of quantities is nothing more 
than their arithmetic sum divided by their number. But the 
utility of an average generally consists in our supposed right to 
substitute, in certain cases, this single measure for the varying 
measures of which it is a function. Sometimes this requires no 
justification ; the word " average " is in these cases used for 
the sake of shortness, and merely to summarise a set of facts : 
as, for instance, when we say that the birth-rate in England is 
greater than the birth-rate in France. 

But there are other cases in which the average makes a more 
substantial claim to add to our knowledge. After a number of 
examiners of equal capacity have given varying marks to a 
candidate for the same paper, it may be thought fair to allow 
the candidate the average of the different marks allotted : and 
in general if several estimates of a magnitude have been made, 


between the accuracy of which we have no reason to discriminate, 
we often think it reasonable to act as if the true magnitude were 
the average of the several measurements. Perhaps De Witt, in 
his report on Annuities to the States General in 1671, 1 was the 
first to use it scientifically. But as Leibniz points out : " Our 
peasants have made use of it for a long time according to their 
natural mathematics. For example, when some inheritance or 
land is to be sold, they form three bodies of appraisers ; these 
bodies are called Schurzen in Low Saxon, and each body makes 
an estimate of the property in question. Suppose, then, that 
the first estimates its value to be 1000 crowns, the second, 1400, 
the third, 1500 ; the sum of these -three estimates is taken, viz. 
3900, and because they were three bodies, the third, i.e. 1300, is 
taken as the mean value asked for. This is the axiom : aequali- 
Iws aequalia, equal suppositions must have equal consideration." 2 

But this is a very inadequate axiom. Equal suppositions 
would have equal consideration, if the three estimates had been 
multiplied together instead of being added. The truth is that 
at all times the arithmetic mean has had simplicity to recommend 
it. It is always easier to add than to multiply. But simplicity 
is a dangerous criterion : " La nature," says Fresnel, " ne s'est 
pas embarass6e des difficult^ d' analyse, elle n'a evite que la 
complication des moyens." 

"With Laplace and Gauss there began a series of attempts to 
'prove the worth of the arithmetic mean. It was discovered that 
its use involved the assumption of a particular type of law of 
error for the a priori probabilities of given errors. It was also 
found that the assumption of this law led on to a more com- 
plicated rule, known as the Method of Least Squares, for com- 
bining the results of observations which contain more than one 
doubtful quantity. In spite of a popular belief that, whilst the 
Arithmetic Mean is intuitively obvious, the Method of Least 
Squares depends upon doubtful and arbitrary assumptions, it 
can be demonstrated that the two stand and fall together. 3 

1 De vardye van de hf-renten na proportie van de losrenten. The Hague, 1671. 

* Nouveaux Essais. EngL transL p. 540. 

3 Venn (Logic of Cliance, p. 40) thinks that the Normal Law of Error and 
the Hethod of Least Squares " are not only totally distinct things, but they have 
scarcely even any necessary connection with each other. The Law of Error 
is the statement of a physical fact. . . . The Method of Least Squares, on the 
other hand, is not a law at all in the scientific sense of the term. It is simply 
a rule or direction. . . ." 


The analytical theorems of Laplace and Gauss are complicated, 
but the special assumptions upon which they are based are easily 
stated. 1 Gauss supposes (a) that the probability of a given error 
is a function of the error only and not also of the magnitude of 
the observation, (&) that the errors are so small that their cubes 
and higher powers may be neglected. Assumption (a) is arbi- 
trary, 2 and Gauss did not state it explicitly. These two assump- 
tions, together with certain others, lead us to the result. For 
let <f)(z) be the law of error where z is the error, and let us assume, 
as it always is assumed in these proofs, that <p(z) can be expanded 

by Maclaurin's Theorem. Then $()=<(0) + 2^(0) + 0*(0) + 



(/>'"(o) + . . . It is also supposed that positive and negative 

o \ 

errors are equally probable, i.e. <f>(z)=<j>(-z), so that <'(<)) and 
<'"(0) vanish. Since we may neglect z 4 in comparison with z 2 , 
+Jz 2 <"(0). But (neglecting z 4 and higher powers) 

ae~* 3 so that <(z) 
Gauss's proof looks much more complicated than this, but he 


obtains the form ae by neglecting higher powers of z, so that 
this expression is really equivalent to a+bz 2 . By this approxi- 
mation he has reduced all the possible laws to an equivalent 
form. 3 It is true, therefore, that the normal law of error is, to 
the second power of the error, equivalent to any law of error, 
which is a function of the error only, and for which positive and 
negative errors are equally probable. Laplace also introduces 
assumptions equivalent to these. 

While mathematicians have endeavoured to establish, the 
normal law of error and the arithmetic mean as a law of logic, 

1 For an account of the three principal methods of arriving at the Method 
of Least Squares and the Arithmetic Mean, see "Ellis, Least Squares. Gauss's 
first method is in the TJieoria Matiis, and his second in the Theoria Cambina- 
ti&nis Observationum. Laplace's investigations are in chap. iv. of the second 
Book of the Theorie analytigue. Laplace's method was improved hy Poisson 
in the GonnaissaTice dea temps for 1827 and 1832. 

2 It does not follow, as G. Hagen argues (Grundz&ge d&r Wahrscheirilichkeite- 
rechnung, p. 29), that, because a larger error is less probable than a smaller, 
therefore the probability of a given error is a function of its magnitude 

8 This is pointed out by Bertrand, Cdlcul des probabtlite.% p 267. 


others have claimed for it the testimony of experience and have 
deemed it a law of nature. 1 

That this cannot be so, is evident. For suppose that x^ 2 . . . x 
are a set of observations of an unknown quantity x. Then, by 

this principle, x = -'Zx r gives the most probable value of x. But 

suppose we had wished to determine x 2 , our observations, assum- 
ing that we can multiply correctly, would be x-f, x. 2 2 . . . x n 2 9 

and the most probable value of x*=-%x r 2 . B ^ (iSav) 2 * -2z r 2 . 

n n n 

And in general, -^f(x r ) =*=/( %x r ). Nor is this a consideration 
n n 

which can safely be ignored in practice. For our "observations" 
are often the result of some manipulation, and the particular 
shape in which we get them is not necessarily fixed for us. It is 
not easy to say what the direct observation is. In particular if 
any such law of sensation, as that enunciated by Fechner, is true 
(i.e. that sensation varies as the logarithm of the stimulus), the 
arithmetic mean must break down as a practical rule in all cases 
where human sensation is part of the instrument by means of 
which the observations are recorded. 2 

Apart, however, from theoretical refutations, statisticians now 
recognise that the arithmetic mean and the normal law of error 
can only be applied to certain special classes of phenomena. 
Quetelet 3 was, I think, the first to point this out. In England, 
Galton drew attention to the fact many years ago, and Professor 
Pearson 4 has shown "that the Gaussian-Laplace normal dis- 
tribution is very far from being a general law of frequency 
distribution either for errors of observation or for the distribution 
of deviations from type such as occur in organic populations. . . . 
It is not even approximately correct, for example, in the distribu- 
tion of barometric variations, of grades of fertility and incidence 
of disease.** 

1 This is, of course, a very common point of view indeed. Of. Bertrand, 
op. cit. p. 183: "Malgre les objections precedentes, la formule de Gauss doit 
etre adoptee. L'observation la confirme : cela doit suffire dans les applications." 

2 This was noticed by Galton. 

3 E.g. Letters on the Theory of Probabilities, p. 114. 

4 On " Errors of Judgment, etc.," Phil Trans. A, voL cxcviii. pp. 235-299. 
The following quotation is from his memoir On the General Theory of Skew 
Correlation and Nonlinear Regression, where further references are given. 


The Arithmetic Mean occupies, therefore, no unique position ; 
and it is worth while, from the point of view of probability, to 
discuss the properties of other possible means and laws of error, 
as, for example, on the lines indicated in the earlier part of this 

10. The Method of Least Squares. The problem, to which this 
method is applied, is no more than the application of the same 
considerations, as those which we have just been discussing, to 
cases where the relation between the observed measurements and 
the quantity whose most probable value we require, involves 
more than one unknown. 

Owing to the surprising character of its conclusions, if they 
could be accepted as universally valid, and to the obscurity of 
the mathematical fabric that has been reared on and about it, 
this method has been surrounded by an unnecessary air of 
mystery. It is true that in recent times scepticism has grown 
at the expense of mystery. It is also true that just views have 
been held by individuals for sixty years past, notably by Leslie 
Ellis. But the old mistakes are not always corrected in the 
current text-books, and even so useful and generally used a 
treatise on Least Squares, as Professor Mansfield Merriman's, 
opens with a series of very fallacious statements. 

The controversial side of the Method of Least Squares is 
purely logical ; in the later developments there is much elaborate 
mathematics of whose correctness no one is in doubt. What it 
is important to state with the utmost possible clearness is the 
precise assumptions on which the mathematics is based ; when 
these assumptions have been set forth, it remains to determine 
their applicability in particular cases. 

In dealing with averages we supposed ourselves to be pre- 
sented with a number of direct observations of some quantity 
which it is desired to determine. But it is obvious that direct 
observations will be in many cases either impracticable or in- 
convenient ; and our natural course will be to measure certain 
other quantities which we know to bear fixed and invariable 
relations to the unknowns we wish to determine. In surveying, 
for instance, 'or in astronomy, we constantly prefer to take 
measurements of angles or distances in which we are not interested 
for their own sakes, but which bear known geometrical relation- 
ships to the set of ultimate unknowns. 



If we wish to determine tlie most probable values of a set of 
unknowns x ly x& X B . . . x r , instead of obtaining a number of 
sets of direct observations of each, we may obtain a number of 
equations of observation of the following type : 

where V l5 etc., are the quantities directly observed, and the a's, 
b's, etc., are supposed known (n>r). 

We have in such a case n equations to determine r unknowns, 
and since the observations are likely to be inexact, there may be 
no precise solution whatever. In these circumstances we wish to 
know the most probable set of values of the o?'s warranted by 
these observations. 

The problem is precisely similar in kind to that dealt with 
by averages and differs only in the degree of its complexity. It 
is the problem of finrh'ng the most probable solution of such a set 
of discrepant equations of observation that the Method of Least 
Squares claims to solve. 

By 1750 the astronomers were obtaining such equations of 
observation in the course of their investigations, and the question 
arose as to the proper manner of their solution. Boscovich in 
Italy, Mayer and Lambert in Germany, Laplace in France, Euler 
in Russia, and Simpson in England proposed different methods 
of solution. Simpson, in 1757, was the first to introduce, by way 
of simplification, the assumption or axiom that positive and 
negative errors are equally probable. 1 The Method of Least 
Squares was first definitely stated by Legendre in 1805, who 
proposed it as an advantageous method of adjusting observations. 
This was soon followed by the * proofs ' of Laplace and Gauss. 
But it is easily shown that these proofs involve the normal law 
of error ^=Jfce~ A%;3 , and the theory of Least Squares simply 
develops the mathematical results of applying to equations of 
observation, whic^L involve more than one unknown, that law 

1 See Memman's Method of Least Squares, p. 181, for an historical sketch, 
from which the above is taken. In 1877 Merriman published in the Trans- 
actions of like Connecticut Academy a list of writings relating to the Method of 
Least Squares and the theory of accidental errors of observation, which com- 
prised 408 titles classified as 313 memoirs, 72 books, 23 parts of books. 


of error which leads to the Arithmetic Mean in the case of a single 

11. The Weighting of Averages. It is necessary to recur to 
the distinction made at the beginning of 9 between the two 
types to which our average, or, as it is generally termed in social 
inquiries, our index number, may belong. The average or index 
number may simply summarise a set of facts and give us the 
actual value of a composite quantity, as, for example, the index 
number of the cost of living. In such cases the composite 
quantity, in which we are interested, need not contain precisely 
the same number of units of each of the elementary quantities of 
which it is composed, so that the e weights/ which denote the 
numbers of each elementary quantity appropriate to the com- 
posite quantity, are part of the definition of the composite 
quantity, and can no more be dispensed with than the magnitudes 
of the elementary quantities themselves. Nor in such cases is 
the rejection of discordant observations permissible ; if, that is 
to say, some of the elementary quantities are subject to much 
wider variation, or to variations of a different type than the 
majority, that is no reason for rejecting them. 

On the other hand, the individual items, out of which the 
average is composed, may each be indications or approximate 
estimates of some one single quantity ; and the average, instead 
of representing the measure of a composite quantity, may be 
selected as furnishing the most probable value of the single 
quantity, given, as evidence of its magnitude, the values of the 
various terms which make up the average. 

If this is the character of our average, the problem of weighting 
depends upon what we know about the individual observations 
or samples or indications, out of which our average is to be built 
up. The units in question may be known to differ in respects 
relevant to the probable value of the quaesitum. Thus there 
may be reasons, quite apart from the actual results of the indi- 
vidual observations or samples, for trusting some of them more 
than others. Our knowledge may indicate to us, in fact, that 
the constants of the laws of error appropriate to the several 
instances, even if the type of the law can be assumed to be 
constant, should be varied according to the data we possess about 
each. It may also indicate to us that the condition of independ- 
ence between the instances, which the method of averages 


presumes, is imperfectly satisfied, and consequently that our 
mode of combining the instances in an average must be modified 

Some modern statisticians, who, really influenced perhaps by 
practical considerations, have been inclined to deprecate the 
importance of weighting on theoretical grounds, have not always 
been quite clear what kind of average they supposed themselves 
to be dealing with. In particular, discussions of the question of 
weighting in connection with index numbers of the value of 
money have suffered from this confusion. It has not been clear 
whether such index numbers really represent measures of a 
composite quantity or whether they are probable estimates of 
the value of a single quantity formed by combining a number of 
independent approximations towards the value of this quantity. 
The original Jevonian conception of an index number of the 
value of money was decidedly of the latter type. Modern work 
on the subject has been increasingly dominated by the other 
conception. A discussion of where the truth lies would lead me 
too far into the field of a subject-matter alien to that of this 

Theoretical arguments against weighting have sometimes 
been based on the fact that to weight the items of the average 
in an irrelevant manner, or, as it is generally expressed, in a 
random manner, is not likely, provided the variations between 
the weights are small compared with the variations between the 
items, to affect the result very much. But why should any one 
wish to weight an average " at random " 1 Such observations 
overlook the real meaning and significance of weights. They are 
probably inspired by the fact that a superficial treatment of 
statistics would sometimes lead to the introduction of weights 
which are irrelevant. In drawing a conclusion, for example, 
from the vital statistics of various towns, the figures of population 
for the different towns may or may not be relevant to our con- 
clusion. It depends on the character of the argument. If they 
are relevant, it may be right to employ them as weights. If they 
are irrelevant, it must be wrong and unnecessary to do so. The 
fact that wheat is a more important article of consumption than 
pins may, on certain assumptions, be irrelevant to the usefulness 
of variations in the price of each article as indications of variation 
in the value of money. With other assumptions, it may be 


extremely relevant. Or again, we may know that observations 
with a particular instrument tend to be too large and must, 
therefore, be weighted down. It is contrary both to theory and 
to common sense to suppose that the possession of information 
as to the relative reliability of different statistics is not useful. 
There is no place, therefore, in my judgment, for a generalised 
argument as to the propriety or impropriety of weighting an 

It should be added that, where we seek to build up an index 
number of a conception, which is quantitative but is not itself 
numerically measurable in any denned or unambiguous sense, by 
combining a number of numerical quantities, which, while they 
do not measure our quaesitum are nevertheless indications of its 
quantitative variations and tend to fluctuate in the same sense, 
as, for example, by means of what are sometimes called economic 
barometers of the state of business, or the prosperity of the country 
or the like, some very confusing questions can arise both as to 
what sort of a thing our resulting index really is, and as to the 
mode of compilation appropriate to it. 

These confusing questions always arise when, instead of 
measuring a quantity directly, we seek an index to fluctuations 
in its magnitude by combining in an average the fluctuations of 
a series of magnitudes, which are, each of them in a different way, 
to some extent (but only to some extent), correlated with fluctua- 
tions in our quaesitum. I must not burden this book with a 
discussion of the problems of Index Numbers. But I venture to 
think that they would be sooner cleared up if the natures and 
purposes of differing index numbers were more sharply distin- 
guished those, namely, which are simply descriptive of a composite 
commodity, those which seek to combine results differing from 
one another in a way analogous to the variations of an instrument 
of precision, and those which combine results, not of the quaesitum 
itself, but of various other quantities, variations in which are 
partly due to variations in the quaesitum, but which we well 
know to be also due to other distinguishable influences. Index 
numbers of the third type are often treated by methods and 
arguments only appropriate to those of the second type. 

12. The Rejection of Discordant Observations. This differs 
from the problem just discussed, because we have supposed so 
far that our system of weighting is determined by data which we 


possess prior to and apart from our knowledge of the actual 
magnitude of the items of our average. The principle of the 
rejection of discordant observations comes in when it is argued 
that, if one or more of our observations show great discrepancies 
from the results of the greater number, these ought to be partly 
or entirely neglected in striking the average, even if there is no 
reason, except their discrepancy from the rest, for attributing 
less weight to them than to the others. By some this practice 
has been thought to be in accordance with the dictates of common 
sense ; by others it is denounced as savouring even of forgery. 1 

This controversy, like so many others in Probability, is due 
to a failure to understand the meaning of ' independence.' The 
mathematics of the orthodox theory of Averages and Least 
Squares depend, as we have seen, upon the assumption that the 
observations are ' independent ' ; but this has sometimes been 
interpreted to mean a physical independence. In point of fact, 
the theory requires that the observations shall be independent, 
in the sense that a knowledge of the result of some does not affect 
the probability that the others, when known, involve given 

Clearly there may be initial data in relation to which this 
supposition is entirely or approximately accurate. But in many 
cases the assumption will be inadmissible. A knowledge of the 
results of a number of observations may lead us to modify our 
opinion as to the relative reliabilities of others. 

The question, whether or not discordant observations should 
be specially weighted down, turns, therefore, upon the nature of 
the preliminary data by which we have been guided in initially 
adopting a particular law of error as appropriate to the observa- 
tions. If the observations are, relevant to these data, strictly 
* independent,' in the sense required for probability, then rejection 
is not permissible. But if this condition is not fulfilled, a bias 
against discordant observations may be well justified. 

1 JB.ff. G. Hagen's Grundz&ge der Wahrscheinlichkeitsrechnung, p. 63 : u Die 
Timschung, die man durch Verschweigen von Messungen begeht, lasst sich 
eben so wenig entsclraldigen, als wenn man Messungen f alschen oder fingiren 





Nothing so like as egg 1 ? ; yet no one, on account of this apparent similarity, 
expects the same taste and relish in all of them. 'Tis only after a long course 
of uniform experiments in any kind, that we attain a firm reliance and security 
with regard to a particular event. Now where is that process of reasoning, 
which from one instance draws a conclusion, so different from that which it 
infers from a hundred instances, that are no way different from that single 
instance 1 This question I propose as much for the sake of information, as 
with any intention of raising difficulties. I cannot find, I cannot imagine any 
such reasoning. But I keep my mind still open to instruction, if any one will 
vouchsafe to bestow it on me. 

1. I HAVE described Probability as comprising that part of 
logic which deals with arguments which are rational but not 
conclusive.- By far the most important types of such arguments 
are those which are based on the methods of Induction and 
Analogy. Almost all empirical science rests on these. And the 
decisions dictated by experience in the ordinary conduct of life 
generally depend on them. To the analysis and logical justifica- 
tion of these methods the following chapters are directed. 

Inductive processes have formed, of course, at all times a 
vital, habitual part of the mind's machinery. Whenever we learn 
by experience, we are using them. But in the logic of the schools 
they have taken their proper place slowly. No clear or satis- 
factory account of them is to be found anywhere. Within and 
yet beyond the scope of formal logic, on the line, apparently, 
between mental and natural philosophy, Induction has been 
admitted into the organon of scientific proof, without much help 
from the logicians, no one quite knows when. 

2. What are its distinguishing characteristics 1 What are 
the qualities which in ordinary discourse seem, to afford strength 
to an inductive argument 1 

1 Philosophical Essays concerning Human Understanding* 


I shall try to answer these questions before I proceed to 
the more fundamental problem What ground have we for re- 
garding such arguments as rational ? 

Let the reader remember, therefore, that in the first of the 
succeeding chapters my main purpose is no more than to state 
in precise language what elements are commonly regarded as 
adding weight to an empirical or inductive argument. This 
requires some patience and a good deal of definition and special 
terminology. But I do not think that the work is controversial. 
At any rate, I am satisfied myself that the analysis of Chapter 
XIX. is fairly adequate. 

In the next section, Chapters XX. and XXL, I continue in 
part the same task, but also try to elucidate what sort of assump- 
tions, if we could adopt them, lie behind and are required by the 
methods just analysed. In Chapter XXII. the nature of these 
assumptions is discussed further, and their possible justification 
is debated, 

3. The passage quoted from Hume at the head of this chapter 
is a good introduction to our subject. Nothing so like as eggs, 
and after a long course of uniform experiments we can expect 
with a firm reliance and security the same taste and relish in all 
of them. The eggs must be like eggs, and we must have tasted 
many of them. This argument is based partly upon Analogy 
and partly upon what may be termed Pure Induction. "We argue 
from Analogy in so far as we depend upon the likeness of the eggs, 
and from Pure Induction when we trust the number of the ex- 

It will be useful to call arguments inductive which depend 
in any way on the methods of Analogy and Pure Induction. But 
I do not mean to suggest by the use of the term inductive that these 
methods are necessarily confined to the objects of phenomenal 
experience and to what are sometimes called empirical questions ; 
or to preclude from the outset the possibility of their use in 
abstract and metaphysical inquiries. While the term inductive 
will be employed in this general sense, the expression Pure 
Induction must be kept for that part of the argument which 
arises out of the repetition of instances. 

4. Hume's account, however, is incomplete. His argument 
could have been improved. His experiments should not have 
been too uniform, and ought to have differed from one another 


as much as possible in all respects save that of the likeness of the 
eggs. He should have tried eggs in the town and in the country, 
in January and in June. He might then have discovered that 
eggs could be good or bad, however like they looked. 

This principle of varying those of the characteristics of the 
instances, which we regard in the conditions of our generalisation 
as non-essential, may be termed Negative Analogy. 

It will be argued later on that an increase in the number of 
experiments is only valuable in so far as, by increasing, or possibly 
increasing, the variety found amongst the non-essential char- 
acteristics of the instances, it strengthens the Negative Analogy. 
If Hume's experiments had been absolutely uniform, he would 
have been right to raise doubts about the conclusion. There is 
no process of reasoning, which from one instance draws a con- 
clusion different from that which it infers from a hundred in- 
stances, if the latter are known to be in no way different from 
the former. Hume has unconsciously misrepresented the typical 
inductive argument. 

When our control of the experiments is fairly complete, and 
the conditions in which they take place are well known, there is 
not much room for assistance from Pure Induction. If the 
Negative Analogies are known, there is no need to count the 
instances. But where our control is incomplete, and we do not 
know accurately in what ways the instances differ from one 
another, then an increase in the mere number of the instances 
helps the argument. For unless we know for certain that the 
instances are perfectly uniform, each new instance may possibly 
add to the Negative Analogy. 

Hume might also have weakened his argument. He expects 
no more than the same taste and relish from his eggs. He 
attempts no conclusion as to whether his stomach will always 
draw from them the same nourishment. He has conserved the 
force of his generalisation by keeping it narrow. 

5. In an inductive argument, therefore, we start with a 
number of instances similar in some respects AB, dissimilar in 
others C. We pick out one or more respects A in which the 
instances are similar, and argue that some of the other respects 
B in which they are also similar are likely to be associated with 
the characteristics A in other unexamined cases. The more 
comprehensive the essential characteristics A, the greater the 


variety amongst tlie non-essential characteristics C, and the less 
comprehensive the characteristics B which we seek to associate 
with A, the stronger is the likelihood or probability of the general- 
isation we seek to establish. 

These are the three ultimate logical elements on which the 
probability of an empirical argument depends, the Positive 
and the Negative Analogies and the scope of the generalisation. 

6. Amongst the generalisations arising out of empirical 
argument we can distinguish two separate types. The first of 
these may be termed universal induction. Although such in- 
ductions are themselves susceptible of any degree of probability, 
they affirm invariable relations. The generalisations which they 
assert, that is to say, claim universality, and are upset if a 
single exception to them can be discovered. Only in the more 
exact sciences, however, do -we aim at establishing universal 
inductions. In the majority of cases we are content with that 
other kind of induction which leads up to laws upon which 
we can generally depend, but which does not claim, however 
adequately established, to assert a law of more than probable 
connection. 1 This second type may be termed Inductive Correla- 
tion. If, for instance, we base upon the data, that this and that 
and those swans are white, the conclusion that all swans are white, 
we are endeavouring to establish a universal induction. But if 
we base upon the data that this and those swans are white and 
that swan is black, the conclusion that most swans are white, 
or that the probability of a swan's being white is such and such, 
then we are establishing an inductive correlation. 

Of these two types, the former universal induction. pre- 
sents both the simpler and the more fundamental problem. In 
this part of my treatise I shall confine myself to it almost entirely. 
In Part V., on the Foundations of Statistical Inference, I shall 
discuss, so far as I can, the logical basis of inductive correlation. 

7. The fundamental connection between Inductive Method 
and Probability deserves all the emphasis I can give it. Many 
writers, it is true, have recognised that the conclusions which we 
reach by inductive argument are probable and inconclusive. 
Jevons, for instance, endeavoured to justify inductive processes 
by means of the principles of inverse probability. And it is true 
also that much of the work of Laplace and his followers was 

1 What Mill calls e approximate generalisations.' 


directed to the solution of essentially inductive problems. But 
it has been seldom apprehended clearly, either by these writers 
or by others, that the validity of every induction, strictly inter- 
preted, depends, not on a matter of fact, but on the existence of 
a relation of probability. An inductive argument affirms, not 
that a certain matter of fact is so, but that relative to certain 
evidence there is a probability in its favour. The validity of the 
induction, relative to the original evidence, is not upset, therefore, 
if, as a fact, the truth turns out to be otherwise. 

The clear apprehension of this truth profoundly modifies 
our attitude towards the solution of the inductive problem. The 
validity of the inductive method does not depend on the success 
of its predictions. Its repeated failure in the past may, of course, 
supply us with new evidence, the inclusion of which will modify 
the force of subsequent inductions. But the force of the old 
induction relative to the old evidence is untouched. The evidence 
with which our experience has supplied us in the past may have 
proved misleading, but this is entirely irrelevant to the 
question of what conclusion we ought reasonably to have 
drawn from the evidence then before us. The validity and 
reasonable nature of inductive generalisation is, therefore, a 
question of logic and not of experience, of formal and not of 
material laws. The actual constitution of the phenomenal 
universe determines the character of our evidence ; but it cannot 
determine what conclusions given evidence rationally supports. 



All kinds of reasoning from causes or effects are founded on two particulars, 
viz. the constant conjunction of any two objects in all past experience, and the 
resemblance of a present object to any of them. Without some degree of 
resemblance, as well as union, 'tis impossible there can be any reasoning. 


1. HUME rightly maintains that some degree of resemblance 
must always exist between the various instances upon which a 
generalisation is based. For they must have this, at least, in 
common, that they are instances of the proposition which 
generalises them. Some element of analogy must, therefore, 
lie at the base of every inductive argument. In this chapter I 
shall try to explain with precision the meaning of Analogy, and 
to analyse the reasons, for which, rightly or wrongly, we usually 
regard analogies as strong or weak, without considering at present 
whether it is possible to find a good reason for our instinctive 
principle that likeness breeds the expectation of likeness. 

2. There are a few technical terms to be defined. We mean 
by a generalisation a statement that all of a certain definable class 
of propositions are true. It is convenient to specify this class 
in the following way. If f(x) is true for all those values of x for 
which fj>(x) is true, then we have a generalisation about <f> and / 
which we may write g((f>, /). If, for example, we are dealing with 
the generalisation, " All swans are white," this is equivalent to 
the statement, " * x is white ' is true for all those values of x for 
which e x is a swan * is true." The proposition <j>(a) ,f(a) is an 
instance of the generalisation g(<f>, f). 

By thus defining a generalisation in terms of prepositional 
functions, it becomes possible to deal with all kinds of generalisa- 

1 A Treatise of Human Nature. 


tions in a uniform way ; and also to bring generalisation into 
convenient connection with, our definition of Analogy. 

If some one thing is true about both of two objects, if, that is 
to say, they both satisfy the same propositional function, then to 
this extent there is an analogy between them. Every generalisa- 
tion #(<,/), therefore, asserts that one analogy is always accom- 
panied by another, namely, that between all objects having the 
analogy < there is also the analogy /. The set of propositional 
functions, which are satisfied by both of the two objects, con- 
stitute the positive analogy. The analogies, which would be 
disclosed by complete knowledge, may be termed the total positive 
analogy ; those which are relative to partial knowledge, the 
known positive analogy. 

As the positive analogy measures the resemblances, so the 
negative analogy measures the differences between the two objects. 
The set of functions, such that each is satisfied by one and not 
by the other of the objects, constitutes the negative analogy. 
We have, as before, the distinction between the total negative 
analogy and the known negative analogy. 

This set of definitions is soon extended to the cases in which 
the number of instances exceeds two. The functions which are 
true of all of the instances constitute the positive analogy of the 
set of instances, and those which are true of some only^ and are 
false of others, constitute the negative analogy. It is clear that 
a function, which represents positive analogy for a group of 
instances taken out of the set, may be a negative analogy for the 
set as a whole. Analogies of this kind, which are positive for 
a sub-class of the instances, but negative for the whole class, we 
may term sub-analogies. By this it is meant that there are 
resemblances which are common to some of the instances, but 
not to all. 

A simple notation, in accordance with these definitions, will 
be useful. If there is a positive analogy < between a set of in- 
stances 0} . . . a n> whether or not this is the total analogy 
between them, let us write this 

A .i 

1 Hence A (^s^). ffo).. . #M= n 

ax... an s=a 


And if there is a negative analogy <', let us write tliis 


fll . . . a n 

Thus A (<) expresses the fact that there is a set of 

GLi . . . a n 

characteristics <f> which are common to all the instances, and 
A (</) that there is a set of characteristics <' which is 

ai . . . a 

true of at least one of the instances and false of at least one. 

3, In the typical argument from analogy we wish to generalise 
from one part to another of the total analogy which experience 
has shown to exist between certain selected instances. In all the 
cases where one characteristic <f> has been found to exist, another 
characteristic/ has been found to be associated with it. We argue 
from this that any instance, which is known to share the first 
analogy <, is likely to share also the second analogy/. We have 
found in certain cases, that is to say, that both < and/ are true 
of them ; and we wish to assert/ as true of other cases in which 
we have only observed 9. We seek to establish the generalisation 
g((j>,f), on the ground that < and /constitute between them an 
observed positive analogy in a given set of experiences. 

But while the argument is of this character, the grounds, upon 
which we attribute more or less weight to it, are often rather 
complex ; and we must discuss them, therefore, in a systematic 

4, According to the view suggested in the last chapter, the 
value of such an argument depends partly upon the nature of the 
conclusion which we seek to draw, partly upon the evidence 
which supports it. If Hume had expected the same degree of 
nourishment as well as the same taste and relish from all of the 
eggs, he would have drawn a conclusion of weaker probability. 
Let us consider, then, this dependence of the probability upon the 
scope of the generalisation g(<f>,f), upon the comprehensiveness, 
that is to say, of the condition <j> and the conclusion/ respectively. 

The more comprehensive the condition $ and the less com- 
prehensive the conclusion /, the greater d priori probability do 
we attribute to the generalisation g. With every increase in < 
this probability increases, and with every increase in / it will 

1 Hence A 

* _ 
a r ' 


The condition <(=<i$ 2 ) ^ oiore comprehensive than the 
condition < 13 relative to the general evidence h, if <p 2 is a condition 
independent of ^ relative to h, < 2 being independent of fa, if 
g(^ jL9 <f> z )/h 4= 1, i.e. if, relative to h, the satisfaction of < 2 is not 
inferrible from that of <f>^. 

Similarly the conclusion /( =/i/2) is more comprehensive than 
the conclusion/!, relative to the general evidence h, if / 2 is a con- 
clusion independent of / ls relative to k, i.e. if ^(/isjQA^l- 

If < =<i< 2 nd-f=fif2> "where ^ and < 2 are independent and 
/! and/ 2 are independent relative to h, we have 

ff(4>i, /)/* -*(&&, /) < 

so that g(<f>, A)lh^ 9 (^,, /)/ASs0(fc, f)/h. 

This proves the statement made above. It will be noticed 
that we cannot necessarily compare the a priori probabilities 
of two generalisations in respect of more and less, unless the con- 
dition of the first is included in the condition of the second, and 
the conclusion of the second is included in that of the first. 

We see, therefore, that some generalisations stand initially 
in a stronger position than others. In order to attain a given 
degree of probability, generalisations require, according to their 
scope, different amounts of favourable evidence to support them. 

5. Let us now pass from the character of the generalisation 
d priori to the evidence by which we support it. Since, when- 
ever the conclusion / is complex, i.e. resolvable into the form 
A/2 where #(/ l3 / 2 )/A =N 1, we can express the probability of the 
generalisation #(<,/) as the product of the probabilities of the 
two generalisations #(<&/i, / 3 ) and ff(<f>?fj), we may assume in what 
follows, that the conclusion /is simple and not capable of further 
analysis, without dTTnim'shiTig the generality of our argument. 

We will begin with the simplest case, namely, that which 
arises in the following conditions. First, let us assume that our 
knowledge of the examined instances is complete, so that we know 
of every statement, which is about the examined instances, 
whether it is true or false of each. 1 Second, let us assume that 

1 If ^(a) is a proposition and ^(a) = h . 6(a), where h is a proposition not 
involving a, then we must regard 0(a), not ^(a) as the statement about a. 



all the instances which are known to satisfy tlie condition 6, 
are also known to satisfy the conclusion / of tlie generalisation. 
And third let ns assume that there is nothing which is true of 
all the examined instances and yet not included either in fy or 
in /, i.e. that the positive analogy between the instances is 
exactly co-extensive with the analogy <j>f which is covered by the 

Such evidence as this constitutes what we may term a perfect 
analogy. The argument in favour of the generalisation cannot 
be further improved by a knowledge of additional instances. 
Since the positive analogy between the instances is exactly 
coextensive with the analogy covered by the generalisation, and 
since our knowledge of the examined instances is complete, there 
is no need to take account of the negative analogy. 

An analogy of this kind, however, is not likely to have much 
practical utility ; for if the analogy covered by the generalisa- 
tion, covers the whole of the positive analogy between the instances 
it is difficult to see to what other instances the generalisation can 
be applicable. Any instance, about which everything is true 
which is true of all of a set of instances, must be identical with 
one of them. Indeed, an argument from perfect analogy can 
only have practical utility, if, as will be argued later on, there are 
some distinctions between instances which are irrelevant for the 
purposes of analogy, and if , in a perfect analogy, the positive 
analogy, of which we must take account, need cover only those 
distinctions which are relevant. In this case a generalisation 
based on perfect analogy might cover instances numerically 
distinct from those of the original set. 

The law of the Uniformity of Nature appears to me to amount 
to an assertion that an analogy which is perfect, except that mere 
differences of position in time and space are treated as irrelevant 
is a valid basis for a generalisation, two total causes being re- 
garded as the same if they only differ in their positions in tim< 
or space. This, I think, is the whole of the importance whicl 
this law has for the theory of inductive argument. It involve 
the assertion of a generalised judgment of irrelevance, namely 
of the irrelevance of mere position in time and space to generalisa 
tions which have no reference to particular positions in tim 
and space. It is in respect of such position in time or space tha 
* nature 9 is supposed * uniform/ The significance of the lai 


and the nature of its justification, if any, are further discussed 
in Chapter XXII. 

6. Let us now pass to the type which is next in order of 
simplicity. We will relax the first condition and no longer assume 
that the whole of the positive analogy between the instances is 
covered by the generalisation, though retaining the assumption 
that our knowledge of the examined instances is complete. We 
know, that is to say, that there are some respects in which the 
examined instances are all alike, and yet which are not covered 
by the generalisation. If ^ is the part of the positive analogy 
between the instances which is not covered by the generalisation, 
then the probability of this type of argument from analogy can 
be written 


The value of this probability turns on the comprehensiveness 
of 0!- There are some characteristics ^ common to all the 
instances, which the generalisation treats as unessential, but 
the less comprehensive these are the better. <p^ stands for the 
characteristics in which all the instances resemble one another 
outside those covered by the generalisation. To reduce these 
resemblances between the instances is the same thing as to 
increase the differences between them. And hence any increase 
in the Negative Analogy involves a reduction in the compre- 
hensiveness of <]> When, however, our knowledge of the 
instances is complete, it is not necessary to make separate 
mention of the negative analogy A (</) in the above formula. 

For $ simply includes all those functions about the instances, 
which are not included in <f>$if, and of which the contradictories 
are not included in them ; so that in stating A (^^x/), we 

0,1... a n 

state by implication A (<f> f ) also. 

a^,..a n 

The whole process of strengthening the argument in favour 
of the generalisation g(<f>, f) by the accumulation of further ex- 
perience appears to me to consist *in making the argument 
approximate as nearly as possible to the conditions of a perfect 
analogy, by steadily reducing the comprehensiveness of those 
resemblances ^ between the instances which our generalisation 
disregards. Thus the advantage of additional instances, derived 


from experience, arises not out of their number as such, but out 
of their tendency to limit and reduce the comprehensiveness of 
fa, or, in other words, out of their tendency to increase the negative 
analogy <j> r 9 since fa$> comprise between them whatever is not 
covered by <j>f. The more numerous the instances, the less com- 
prehensive are their superfluous resemblances likely to be. But 
a single additional instance which greatly reduced fa would in- 
crease the probability of the argument more than a large number 
of instances which afiected fa less. 

7. The nature of the argument examined so far is, then, that 
the instances all have some characteristics in common which 
we have ignored in framing our generalisation ; but it is still 
assumed that our knowledge about the examined instances is 
complete. "We will next dispense with this latter assumption, and 
deal with the case in which our knowledge of the characteristics 
of the examined instances themselves is or may be incomplete. 

It is now necessary to take explicit account of the known 
negative analogy. For when the known positive analogy falls 
short of the total positive analogy, it is not possible to infer the 
negative analogy from it. Differences may be known between the 
instances which cannot be inferred from the known positive 
analogy. The probability of the argument must, therefore, be 


where $faf stands for the characteristics in which all n instances 
&! . . . a n are known to be alike, and <fS stands for the char- 
acteristics in which they are known to differ. 

This argument is strengthened by any additional instance or 
by any additional knowledge about the former instances which 
diminishes the known superfluous resemblances fa or increases the 
negative analogy <f>'. The object of the accumulation of further 
experience is still the same as before, namely, to make the form 
of the argument approximate more and more closely to that of 
perfect analogy. Now, however, that our knowledge of the 
instances is no longer assumed to be complete, we must take 
account of the mere number n of the instances, as well as of our 
specific knowledge in regard to them ; for the more numerous 
the instances are, the greater the opportunity for the total 
negative analogy to exceed the Tmown negative analogy. But 


the more complete our knowledge of the instances, the less 
attention need we pay to their mere number, and the more 
imperfect our knowledge the greater the stress which must be 
laid upon the argument from number. This part of the argu- 
ment will be discussed in detail in the following chapter on 
Pure Induction. 

8. When our knowledge of the instances is incomplete, there 
may exist analogies which are known to be true of some of the 
instances and are not known to be false of any. These sub- 
analogies (see 2) are not so dangerous as the positive analogies ^ 
which are known to be true of all the instances, but their existence 
is, evidently, an element of weakness, which we must endeavour 
to eliminate by the growth of knowledge and the multiplication 
of instances. A sub-analogy of this kind between the instances 
a r . . . a s may be written A (i/r fc ) ; and the formula, if it 

a r ... a s 

is to take account of all the relevant information, ought, there- 
fore, to be written 


!... a 

where the terms of II / A (^)\ stand for the various sub- 

analogies between sub-classes of the instances, which are not 
included in <j><f>if or in $ '. 

9. There is now another complexity to be introduced. "We 
must dispense with the assumption that the whole of the analogy 
covered by the generalisation is known to exist in all the instances. 
For there may be some instances within our experience, about 
which our knowledge is incomplete, but which show part of iihe 
analogy required by the generalisation and nothing which, con- 
tradicts it; and such, instances afford some support to the 
generalisation. Suppose that & < and 6 / are part of < and / re- 
spectively, then we may have a set of instances l . . . b m which 
show the following analogies : 

'A <frfca/) A ( 6 ')n/ A ( & t*)\, 

&1...&W &i...&nt \&r...& J 

where ^ is the analogy not covered by the generalisation, and 
so on, as before. 


The formula, therefore, is now as follows : 

<,(<!>,/)/ n / A Lt^f) i (.^inf ... 

/ ,fc. .. Vui.. . u.i !... J ^aA... J 

In this expression a , u /are the whole or part of <,/; tlie product 
II is composed of the positive and negative analogies for each 

a, 6. . . 

of the sets of instances % . . . a. n , b . . . b m , etc. ; and the 
product II contains the various sub-analogies of different sub- 
classes of all the instances a^ . . . a n) b^ . . . b m , etc., regarded as 
one set. 1 

10. This completes our classification of the positive evidence 
which supports a generalisation ; but the probability may also 
be affected by a consideration of the negative evidence. We 
have taken account so far of that part of the evidence only which 
shows the whole or part of the analogy we require, and we have 
neglected those instances of which <, the condition of the general- 
isation, or/, its conclusion, or part of < or of /is known to be false. 
Suppose that there are instances of which < is true and/ false, it 
is clear that the generalisation is ruined. But cases in which we 
know part of < to be true and/ to be false, and are ignorant as 
to the truth or falsity of the rest of 0, weaken it to some extent. 
We must take account, therefore, of analogies 

where a ,<, part of <, is true of all the set, and a ,/, part of /, is 
false of all the set, while the truth or falsity of some part of <p and 
/ is unknown. The negative evidence, however, can strengthen 
as well as weaken the evidence. We deem instances favourably 
relevant in which < and/ are both false together. 2 

Our final formula, therefore, must include terms, similar to 
those in the formula which concludes 9, not only for sets of 
instances which show analogies ^jf, where a < and J are parts 

of <f> and /, but also for sets which show analogies 

1 Even if we want to distinguish between the sub-analogies of the a set and 
the sub-analogies of the b set, this information can be gathered from the pro- 
duct IL 

* I am disposed to think that we need not pay attention to instances for 
which part of is known to be false, and part of / to be true. But the 
question is a little perplexing. 


or analogies a <f> a f, where a (j> and a f are the whole or part of $ 
and/, and </ are the contradictories of <j> and/. 1 

It should be added, perhaps, that the theoretical classifica- 
tion of most empirical arguments in daily use is complicated by 
the account which we reasonably take of generalisations previ- 
ously established. We often take account indirectly, therefore, 
of evidence which supports in some degree other generalisations 
than that which we are concerned to establish or refute at the 
moment, but the probability of which is relevant to the problem 
under investigation. 

11. The argument will be rendered unnecessarily complex, 
without much benefit to its theoretical interest, if we deal with 
the most general case of all. What follows, therefore, will deal 
with the formula of the third degree of generality, namely 

A ( A 

f A to)}, 

(a r . . - a* J 

in which no partial instances occur, i.e. no instances in which part 
only of the analogy, required by the generalisation, is known to 
exist. In this third degree of generality, it will be remembered, 
our knowledge of the characteristics of the instances is in- 
complete, there is more analogy between the instances than is 
covered by the generalisation, and there are some sub-analogies 
to be reckoned with. In the above formula the incompleteness 
of our knowledge is implicitly recognised in that ^i/^' are 
not between them entirely comprehensive. It is also supposed 
that all the evidence we have is positive, no knowledge is 
assumed, that is to say, of instances characterised by the con- 

junctions a < a /, afrj, or a $ a /, where a </> and a/are part of < and/. 
An argument, therefore, from experience, in which, on the 
basis of examined instances, we establish a generalisation applic- 
able beyond these instances, can be strengthened, if we restrict our 
attention to the simpler type of case, by the following means : 

(1) By reducing the resemblances fa known to be common, to 
all the instances, but ignored as unessential by the generalisation. 

(2) By increasing the differences $ f known to exist between 
the instances. 

1 Where the conclusion /is simple and not complex (see 5), some of these 
complications cannot, of course, arise. 


(3) BY fKTTUTURim\g the sub-analogies or unessential resem- 
blances ty, known to be common to some of the instances and not 
known to be false of any. 

These results can generally be obtained in two ways, either by 
increasing the number of our instances or by increasing our know- 
ledge of those we have. 

The reasons why these methods seem to coin in on sens'e to 
strengthen the argument are fairly obvious. The object of (1) is to 
avoid the possibility that fa as well as < is a necessary condition 
of/. The object of (2) is to avoid the possibility that there may 
be some resemblances additional to <, common to all the instances, 
which have escaped our notice. The object of (3) is to get rid 
of indications that the total value of fa may be greater than the 
known value. When $faf is the total positive analogy between 
the instances, so that the known value of fa is its total value, it 
is (1) which is fundamental ; and w^ need take account of (2) 
and (3) only when our knowledge of the instances is incomplete. 
But when our knowledge of the instances is incomplete, so that 
fa falls short of its total value and we cannot infer </ from it, 
it is better to regard (2) as fundamental ; in any case every 
reduction of fa must increase <'. 

12. I have now attempted to analyse the various ways in 
which common practice seems to assume that considerations 
of Analogy can yield us presumptive evidence in favour of a 

It has been my object, in making a classification of empirical 
arguments, not so much to put my results in forms closely similar 
to those in which problems of generalisation commonly present 
themselves to scientific investigators, as to inquire whether 
ultimate uniformities of method can be found beneath the 
innumerable modes, superficially differing from another, in 
which we do in fact argue. 

I have not yet attempted to justify this way of arguing. 
After turning aside to discuss in more detail the method of Pure 
Induction, I shall make this attempt ; or rather I shall try to see 
what sort of assumptions are capable of justifying empirical 
reasoning of this kind. 



1. IT has often been thought that the essence of inductive argu- 
ment lies in the multiplication of instances. " Where is that 
process of reasoning," Hume inquired, cc which from one instance 
draws a conclusion, so different from that which it infers from 
a hundred instances, that are no way different from that single 
instance 1 " I repeat that by emphasising the number of the in- 
stances Hume obscured the real object of the method. If it 
were strictly true that the hundred instances are no way different 
from the single instance, Hume would be right to wonder in what 
manner they can strengthen the argument. The object of in- 
creasing the number of instances arises out of the fact that we 
are nearly always aware of some difference between the instances, 
and that even where the known difference is insignificant we may 
suspect, especially when our knowledge of the instances is very 
incomplete, that there may be more. Every new instance may 
diminish the unessential resemblances between the instances and 
by introducing a new difference increase the Negative Analogy. 
For this reason, and for this reason only, new instances are 

If our premisses comprise the body of memory and tradition 
which has been originally derived from direct experience, and 
the conclusion which we seek to establish is the Newtonian theory 
of the Solar System, our argument is one of Pure Induction, in 
so far as we support the Newtonian theory by pointing to the 
great number of consequences which it has in common with the 
facts of experience. The predictions of the Nautical Almanack 
are a consequence of the Newtonian theory, and these predictions 
are verified many thousand times a day. But even here the 



force of the argument largely depends, not on the mere number 
of these predictions, but on the knowledge that the circumstances 
in which they are fulfilled differ widely from one another in a 
vast number of important respects. The variety of the circum- 
stances, in which the Newtonian generalisation is fulfilled, rather 
than the number of them, is what seems to impress our reasonable 

2. I hold, then, that our object is always to increase the 
Negative Analogy, or, which is the same thing, to diminish the 
characteristics common to all the examined instances and yet not 
taken account of by our generalisation. Our method, however, 
may be one which certainly achieves this object, or it may be one 
which possibly achieves it. The former of these, which is obvi- 
ously the more satisfactory, may consist either in increasing our 
definite knowledge respecting instances examined already, or in 
finding additional instances respecting which definite knowledge 
is obtainable. The second of them consists in finding additional 
instances of the generalisation, about which, however, our de- 
finite knowledge may be meagre ; such further instances, if our 
knowledge about them were more complete, would either increase 
or leave unchanged the Negative Analogy ; in the former case 
they would strengthen the argument and in the latter case they 
would not weaken it ; and they must, therefore, be allowed some 
weight. The two methods are not entirely distinct, because 
new instances, about which we have some knowledge but not 
much, may be known to increase the Negative Analogy a little 
by the first method, and suspected of increasing it further by the 

It is characteristic of advanced scientific method to depend 
on the former, and of the crude unregulated induction of ordinary 
experience to depend on the latter. It is when our definite 
knowledge about the instances is limited, that we must pay 
attention to their number rather than to the specific differences 
between them, and must fall back on what I term Pure Induction. 

In this chapter I investigate the conditions and the manner 
in which the mere repetition of instances can add to the force 
of the argument. The chief value of the chapter, in my judg- 
ment, is negative, and consists in showing that a line of advance, 
which might have seemed promising, turns out to be a blind 
alley, and that we are thrown back on known Analogy. Pure 


Induction will not give us any very substantial assistance in 
getting to the bottom of the general inductive problem. 

3. The problem of generalisation l by Pure Induction can be 
stated in the following symbolic form : 

Let Ji represent the general a priori data of the investigation ; 
let g represent the generalisation which we seek to establish ; 
let x&z . . . x n represent instances of g. 

Then xjgh^l, x^/gh^l . . . xjgh = l ; given g, that is to 
say, the truth of each of its instances follows. The problem is 
to determine the probability g/hx l x 2 . . . x r , i.e. the probability 
of the generalisation when n instances of it are given. Our 
analysis will be simplified, and nothing of fundamental importance 
will be lost, if we introduce the assumption that there is nothing 
in our a priori data which leads us to distinguish between the 
d priori likelihood of the different instances ; we assume, that is 
to say, that there is no reason d priori for expecting the occurrence 
of any one instance with greater reliance than any other, i.e. 






= , and hence p n = . p Q , where p Q =g/h, i.e. 


is the d priori probability of the generalisation. 

1 In the most general sense we can regard any proposition as the generalisa- 
tion of all the propositions which follow from it. ]?or if A is any proposition, 
and we put $(x) == c x can be inferred from A ' and f(x) == x, then g(<f>, /) = H Since 
Pure Induction consists in finding as many instances of a generalisation as 
possible, it is, in the widest sense, the process of strengthening the probability 
of any proposition by adducing numerous instances of known truths which 
follow from it. The argument is one of Pure Induction, therefore, in so far as 
the probability of a conclusion is based upon the number of independent con- 
sequences which the conclusion and the premisses have in common. 


It follows, therefore, that^^,-! so long as 

tfpi'a . . . xjh = -tf lz /Aiia i a . . . x n ^ . z& 2 . . . os M _ 

... = __ 

g/k +&&... x 

This approaches unity as a limit, if xx 2 . . . xJgti . 

approaches zero as a limit, when n increases. 

4 We may now stop to consider how much this argument has 
proved. We have shown that if each of the instances necessarily 
follows from the generalisation, then each additional instance 
increases the probability of the generalisation, so long as the new 
instance could not have been predicted with certainty from a 
knowledge of the former instances. 1 This condition is the same 
as that which came to light when we were discussing Analogy. 
If the new instance were identical with one of the former in- 
stances, a knowledge of the latter would enable us to predict it. 
If it differs or may differ in analogy, then the condition required 
above is satisfied. 

The common notion, that each successive verification of a 
doubtful principle strengthens it, is formally proved, therefore, 
without any appeal to conceptions of law or of causality. But 
we have not proved that this probability approaches certainty as 
a limit, or even iihat our conclusion becomes more likely than not, 
as the number of verifications or instances is indefinitely increased. 

5. What are the conditions which must be satisfied in order 
that the rate, at which the probability of the generalisation 
increases, may be such that it will approach certainty as a 
1 Since Pn^pn-i so long as y w *l. 


limit when the number of independent instances of it are in- 
definitely increased ? We have already shown, as a basis for 
this investigation, that p n approaches the limit of certainty for 
a generalisation g, if, as n increases, XjX 2 . . . xjgh becomes 
small compared with p Q} i.e. if the a priori probability of so many 
instances, assuming the falsehood of the generalisation, is small 
compared with the generalisation's d priori probability. It 
follows, therefore, that the probability of an induction tends 
towards certainty as a limit, when the number of instances is 
increased, provided that 

for all values of r s and^ >77, where e and 77 are finite proba- 
bilities, separated, that is to say, from impossibility by a value 
of some finite amount, however small. These conditions appear 
simple, but the meaning of a c finite probability ' requires a 
word of explanation. 1 

I argued in Chapter III. that not all probabilities have an 
exact numerical value, and that, in the case of some, one can say 
no more about their relation to certainty and impossibility than 
that they fall short of the former and exceed the latter. There 
is one class of probabilities, however, which I called the numerical 
class, the ratio of each of whose members to certainty can be 
expressed by some number less than unity ; and we can sometimes 
compare a non-numerical probability in respect of more and less 
with one of these numerical probabilities. This enables us to 
give a definition of * finite probability * which is capable of applica- 
tion to non-numerical as well as to numerical probabilities. I 
define a e finite probability * as one which exceeds some numerical 
probability, the ratio of which to certainty can be expressed by 
a finite number. 2 The principal method, in which a probability 
can be proved finite by a process of argument, arises either when 

1 The proof of these conditions, which is obvious, is as follows : 

x-pz . . . x n /gh=x n /x l x 2 *..x n -iffh. x^x z . . . x n .Jgh < (1 - e) n , 
where e is finite and PQ>TJ where 77 is finite. There is always, under these 

(1 e) n 
conditions, some finite value of n such that both (1 - e) n and * - &*& tess 

than any given finite quantity, however smalL 

2 Hence a series of probabilities p^ p r approaches a limit L, if, given 
any positive finite number e however small, a positive integer n can always be 
found such that for all values of r greater than n the difference between L and p r 
is less than .7, where y is the measure of certainty. 


its conclusion can be shown to be one of a finite number of alter- 
natives, which are between them exhaustive or, at any rate, have 
a finite probability, and to which the Principle of Indifference 
is applicable ; or (more usually), when its conclusion is more 
probable than some hypothesis which satisfies this first condition. 

6. The conditions, which we have now established in order 
that the probability of a pure induction may tend towards 
certainty as the number of instances is increased, are (1) that 
Xrlxfa ...x r _-$Ti falls short of certainty by a finite amount 
for all values of r, and (2) that p Q , the a priori probability of our 
generalisation, exceeds impossibility by a finite amount. It is 
easy to see that we can show by an exactly similar argument that 
the following more general conditions are equally satisfactory : 

(1) That x r jXiX 2 . - - %r-iffh falls sllort of certainty by a finite 
amount for all values of r beyond a specified value s. 

(2) That fa the probability of the generalisation relative to 
a knowledge of these first s instances, exceeds impossibility by 
a finite amount. 

In other words Pure Induction can be usefully employed to 
strengthen an argument if, after a certain number of instances 
have been examined, we have, from some other source, a finite 
probability in favour of the generalisation, and, assuming the 
generalisation is false, a finite uncertainty as to its conclusion 
being satisfied by the next hitherto unexamined instance which 
satisfies its premiss. To take an example, Pure Induction can 
be used to support the generalisation that the sun will rise every 
morning for the next million years, provided that with the ex- 
perience we have actually had there are finite probabilities, 
however small, derived from some other source, first, in favour of 
the generalisation, and, second, in favour of the sun's not rising 
to-morrow assuming the generalisation to be false. Given these 
finite probabilities, obtained otherwise, however small, then the 
probability can be strengthened and can tend to increase towards 
certainty by the mere multiplication of instances provided 
that these instances are so far distinct that they are not 
inferrible one from another. 

7. Those supposed proofs of the Inductive Principle, which 
are based openly or implicitly on an argument in inverse prob- 
ability, are all vitiated by unjustifiable assumptions relating 
to the magnitude of the d priori probability p Q . Jevons, for 


instance, avowedly assumes that we may, in tlie absence of special 
information, suppose any unexamined hypothesis to be as likely 
as not. It is difficult to see how such a belief, if even its most 
immediate implications had been properly apprehended, could 
have remained plausible to a mind of so sound a practical judg- 
ment as his. The arguments against it and the contradictions 
to which it leads have been dealt with in Chapter IV. The 
demonstration of Laplace, which depends upon the Rule of 
Succession, will be discussed in Chapter XXX. 

8. The prior probability, which must always be found, before 
the method of pure induction can be usefully employed to support 
a substantial argument, is derived, I think, in most ordinary 
cases with what justification it remains to discuss from con- 
siderations of Analogy. But the conditions of valid induction 
as they have been enunciated above, are quite independent of 
analogy, and might be applicable to other types of argument. 
La certain cases we might feel justified in assuming directly that 
the necessary conditions are satisfied. 

Our belief, for instance, in the validity of a logical scheme is 
based partly upon inductive grounds on the number of conclu- 
sions, each seemingly true on its own account, which can be 
derived from the axioms and partly on a degree of self -evidence 
in the axioms themselves sufficient to give them the initial 
probability upon which induction can build. We depend upon 
the initial presumption that, if a proposition appears to us to 
be true, this is by itself, in the absence of opposing evidence, 
some reason for its being as well as appearing true. We cannot 
deny that what appears true is sometimes false, but, unless we 
can assume some substantial relation of probability between 
the appearance and the reality of truth, the possibility of 
even probable knowledge is at an end. 

The conception of our having some reason, though not a 
conclusive one, for certain beliefs, arising out of direct inspection, 
may prove important to the theory of epistemology. The old 
metaphysics has been greatly hindered by reason of its having 
always demanded demonstrative certainty. Much of the cogency 
of Hume's criticism arises out of the assumption of methods 
of certainty on the part of those systems against which it was 
directed. The earlier realists were hampered by their not per- 
ceiving that lesser claims in the beginning might yield them 


what they wanted in the end. And transcendental philosophy 
has partly arisen, I believe, through the belief that there is no 
knowledge on these matters short of certain knowledge, being 
combined with the belief that such certain knowledge of meta- 
physical questions is beyond the power of ordinary methods. 

When we allow that probable knowledge is, nevertheless, real, 
a new method of argument can be introduced into metaphysical 
discussions. The demonstrative method can be laid on one side, 
and we may attempt to advance the argument by taking account 
of circumstances which seem to give some reason for preferring 
one alternative to another. Great progress may follow if the 
nature and reality of objects of perception, 1 for instance, can be 
usefully investigated by methods not altogether dissimilar from 
those employed in science and with the prospect of obtaining as 
high a degree of certainty as that which belongs to some scientific 
conclusions ; and it may conceivably be shown that a belief in 
the conclusions of science, enunciated in any reasonable manner 
however restricted, involves a preference for some metaphysical 
conclusions over oliiers. 

9. Apart from analysis, careful reflection would hardly lead 
us to expect that a conclusion which is based on no other than 
grounds of pure induction, defined as I have defined them as 
consisting of repetition of instances merely, could attain in this 
way to a high degree of probability. To this extent we ought 
all of us to agree with Hume. "We have found that the sugges- 
tions of common sense are supported by more precise methods. 
Moreover, we constantly distinguish between arguments, which 
we call inductive, upon other grounds than the number of in- 
stances upon which they are based ; and under certain conditions 
we regard as crucial an insignificant number of experiments. The 
method of pure induction may be a useful means of strengthening 
a probability based on some other ground. In the case, however, 
of most scientific arguments, which would commonly be called 
inductive, the probability that we are right, when we make 
predictions on the basis of past experience, depends not so 
much on the number of past experiences upon which we rely, 
as on the degree in which the circumstances of these experiences 

1 A paper by Mr. G. E. Moore entitled, " The Nature and Reality of Objects 
of Perception," which was published in the Proceedings of the Aristotelian Society 
for 1906, seems to me to apply for the fijst time a method somewhat resembling 
that which is d8Cjribe4 above, 


resemble the known circumstances in winch the prediction is 
to take effect. Scientific method, indeed, is mainly devoted to 
discovering means of so heightening the known analogy that 
we may dispense as far as possible with the methods of pure 

When, therefore, our previous knowledge is considerable 
and the analogy is good, the purely inductive part of the argu- 
ment may take a very subsidiary place. But when our knowledge 
of the instances is slight, we may have to depend upon pure 
induction a good deal. In an advanced science it is a last resort, 
the least satisfactory of the methods. But sometimes it must 
be our first resort, the method upon which we must depend in 
the dawn of knowledge and in fundamental inquiries where 
we must presuppose nothing. 



1. IN the enunciation, given in the two preceding chapters, of the 
Principles of Analogy and Pure Induction there has been no 
reference to experience or causality or law. So far, the argument 
has been perfectly formal and might relate to a set of proposi- 
tions of any type. But these methods are most commonly 
employed in physical arguments where material objects or 
experiences are the terms of the generalisation. We must con- 
sider, therefore, whether there is any good ground, as some 
logicians seem to have supposed, for restricting them to this 
kind of inquiry. 

I am inclined to think that, whether reasonably or not, we 
naturally apply them to all kinds of argument alike, including 
formal arguments as, for example, about numbers. When we 
are told that Fermat's formula for a prime, namely, 2 2 " -f 1 for 
all values of a, has been verified in every case in which veri- 
fication is not excessively laborious namely, for a = l, 2, 3, 
and 4, we feel that this is some reason for accepting it, or, at 
least, that it raises a sufiicient presumption to justify a 
further examination of the formula. 1 Yet there can be no refer- 
ence here to the uniformity of nature or physical causation. If 
inductive methods are limited to natural objects, there can no 
more be an appreciable ground for thinking that 2 2flt + 1 is a true 
formula for primes, because empirical methods show that it 
yields primes up to a =4, or even if they showed that it yielded 
primes for every number up to a million million, than there is 
to think that any formula which I may choose to write down 

1 This formula has, in fact, been disproved in recent times, e.g. 2 a5 H- 1 = 
4, 294, 967, 297 = 641 x 6, 700, 417. Thus it is no longer so good an illustration 
as it would have heen a hundred years ago. 



at random is a true source of primes. To maintain that there is 
no appreciable ground in such a case is paradoxical. If, on the 
other hand, a partial verification does raise some just appreciable 
presumption in the formula's favour, then we must include 
numbers, at any rate, as well as material objects amongst the 
proper subjects of the inductive method. The conclusion of 
the previous chapter indicates, however, that, if arguments of 
this kind have force, it can only be in virtue of there being 
some finite d priori probability for the formula based on other 
than inductive grounds. 

There are some illustrations in Jevons's Principles of Science?- 
which are relevant to this discussion. We find it to be true of 
the following six numbers : 

5, 15, 35, 45, 65, 95 

that they all end in five, and are all divisible by five without re- 
mainder. Would this fact, by itself, raise any kind of presump- 
tion that all numbers ending in five are divisible by five without 
remainder ? Let us also consider the six numbers, 

7, 17, 37, 47, 67, 97. 

They all end in seven and also agree in being primes. Would 
this raise a presumption in favour of the generalisation that all 
numbers are prime, which end in seven *? We might be prejudiced 
in favour of the first argument, because it would lead us to a 
true conclusion ; but we ought not to be prejudiced against the 
second because it would lead us to a false one ; for the validity 
of empirical arguments as the foundation of a probability cannot 
be affected by the actual truth or falsity of their conclusions* 
If, on the evidence, the analogy is similar and equal, and if the 
scope of the generalisation and its conclusion is similar, then the 
value of the two arguments must be equal also. 

Whether or not the use of empirical argument appears plausible 
to us in these particular examples, it is certainly true that many 
mathematical theorems have actually been discovered by such 
methods. Generalisations have been suggested nearly as often, 
perhaps, in the logical and mathematical sciences, as in the 

1 Pp. 229-231 (one volume edition). Jevons uses these illustrations, not 
for the purpose to which I am here putting them, but to demonstrate the falli- 
bility of empirical laws. 


physical, by the recognition of particular instances, even where 
formal proof has been forthcoming subsequently. Yet if the 
suggestions of analogy have no appreciable probability in the 
formal sciences, and should be permitted only in the material, it 
must be unreasonable for us to pursue them. If no finite prob- 
ability exists that a formula, for which we have empirical verifica- 
tion, is in fact universally true, Newton was acting fortunately, 
but not reasonably, when he hit on the Binomial Theorem by 
methods of empiricism. 1 

2. I am inclined to believe, therefore, that, if we trust the 
promptings of common sense, we have the same kind of ground 
for trusting analogy in mathematics that we have in physics, 
and that we ought to be able to apply any justification of the 
method, which suits the latter case, to the former also. This 
does not mean that the a priori probabilities, from some other 
source than induction, which the inductive method requires as 
its foundation, may not be sought and found differently in the 
two types of inquiry. A reason why it has been thought 
that analogy ought to be confined to natural laws may be, 
perhaps, that in most of those cases, in which we could 
support a mathematical theorem by a very strong analogy, the 
existence of a formal proof has done away with the necessity 
for the limping methods of empiricism ; and because in most 
mathematical investigations, while in our earliest thoughts 
we are not ashamed to consult analogy, our later work will be 
more profitably spent in searching for a formal proof than in 
establishing analogies which must, at the best, be relatively weak. 
As the modern scientist discards, as a rule, the method of pure 
induction, in favour of experimental analogy, where, if he 
takes account of his previous knowledge, one or two cases may 
prove immensely significant; so the modern mathematician 
prefers the resources of his analysis, which may yield "him 
certainty, to the doubtful promises of empiricism. 

3. The main reason, however, why it has often been held that 
we ought to limit inductive methods to the content of the particu- 
lar material universe in which we live, is, most probably, the 
fact that we can easily imagine a universe so constructed that 
such methods would be useless. This suggests that analogy and 
induction, while they happen to be useful to us in this world, 

1 See Jevons, Zoc. tit. p. 231. 


cannot be universal principles of logic, on the same footing, for 
instance, as the syllogism. 

In one sense this opinion may be well founded. I do not deny 
or affirm at present that it may be necessary to confine inductive 
methods to arguments about certain kinds of objects or certain 
kinds of experiences. It may be true that in every useful argu- 
ment from analogy our premisses must contain fundamental 
assumptions, obtained directly and not inductively, which some 
possible experiences might preclude. Moreover, the success of 
induction in the past can certainly affect its probable usefulness 
for the future. We may discover something about the nature 
of the universe we may even discover it by means of induction 
itself the knowledge of which has the effect of destroying the 
further utility of induction. I shall argue later on that the 
confidence with which we ourselves use the method does in 
fact depend upon the nature of our past experience. 

But this empirical attitude towards induction may, on the 
other hand, arise out of either one of two possible confusions. 
It may confuse, first, the reasonable character of arguments 
with their practical usefulness. The usefulness of induction 
depends, no doubt, upon the actual content of experience. If 
there were no repetition of detail in the universe, induction 
would have no utility. If there were only a single object in the 
universe, the laws of addition would have no utility. But the 
processes of induction and addition would remain reasonable. 
It may confuse, secondly, the validity of attributing probability 
to the conclusion of an argument with the question of the actual 
truth of the conclusion. Induction tells us that, on the basis of 
certain evidence, a certain conclusion is reasonable, not that it is 
true. If the sun does not rise to-morrow, if Queen Anne still 
lives, this will not prove that it was foolish or unreasonable of us 
to have believed the contrary. 

4. It will be worth while to say a little more in this connection 
about the not infrequent failure to distinguish the rational from 
the true. The excessive ridicule, which this mistake has visited 
on the supposed irrationality of barbarous and primitive peoples, 
affords some good examples. " Reflection and enquiry should 
satisfy us," says Dr. Frazer in the Golden Bough, " that to our 
predecessors we are indebted for much of what we thought most 
our own, and that their errors were not wilful extravagances 


or the ravings of insanity, but simply hypotheses, justifiable as 
such at the time when they were propounded, but which a fuller 
experience has proved to be inadequate. . . . Therefore, in 
reviewing the opinions and practices of ruder ages and races we 
shall do well to look with leniency upon their errors as inevitable 
slips made in the search for truth. ..." The first introduction of 
iron ploughshares into Poland, he tells in another passage, having 
been followed by a succession of bad harvests, the farmers attri- 
buted the badness of the crops to the iron ploughshares, and dis- 
carded them for the old wooden ones. The method of reasoning 
of the farmers is not different from that of science, and may, 
surely, have had for them some appreciable probability in its 
favour. " It is a curious superstition," says a recent pioneer in 
Borneo, " this of the Dusuns, to attribute anything whether 
good or bad, lucky or unlucky that happens to them to some- 
thing novel which has arrived in their country. For instance, 
my living in Kindram has caused the intensely hot weather we 
have experienced of late." 1 What is this curious superstition 
but the Method of Difference ? 

The following passage from Jevons's Principles of Science well 
illustrates the tendency, to which he himself yielded, to depreci- 
ate the favourite analogies of one age, because the experience of 
their successors has confuted them. Between things which are 
the same in number, he points out, there is. a certain resemblance, 
namely in number ; and in the infancy of science men could not 
be persuaded that there was not a deeper resemblance implied 
in that of number. " Seven days are mentioned in Genesis ; 
infants acquire their teeth at the end of seven months ; they 
change them at the end of seven years ; seven feet was the limit 
of man's height ; every seventh year was a climacteric or critical 
year, at which a change of disposition took place. In natural 
science there were not only the seven planets, and the seven 
metals, but also the seven primitive colours, and the seven tones 
of music. So deep a hold did this doctrine take that we still have 
its results in many customs, not only in the seven days of the 
week, but the seven years* apprenticeship, puberty at fourteen 
years, the second climacteric, and legal majority at twenty-one 
years, the third climacteric." Religious systems from Pythagoras 
to Comte have sought to derive strength from the virtue of seven. 
1 Golden Bough, p. 174. 


" And even in scientific matters the loftiest intellects have occa- 
sionally yielded, as when Newton was misled by the analogy 
between the seven tones of music and the seven colours of his 
spectrum. . . . Even the genius of Huyghens did not prevent 
him from inferring that but one satellite could belong to Saturn, 
because, with those of Jupiter and the earth, it completed the 
perfect number of six." But is it certain that Newton and 
Huyghens were only reasonable when their theories were true, 
and that their mistakes were the fruit of a disordered fancy 1 
Or that the savages, from whom we have inherited the most 
fundamental inductions of our knowledge, were always super- 
stitious when they believed what we now know to be 
preposterous ? 

It is important to understand that the common sense of the 
race has been impressed by very weak analogies and has attri- 
buted to them an appreciable probability, and that a logical 
theory, which is to justify common sense, need not be afraid of 
including these marginal cases. Even our belief in the real 
existence of other people, which we all hold to be well estab- 
lished, may require for its justification the combination of 
experience with a just appreciable d priori possibility for 
Animism generally. 1 If we actually possess evidence which 
renders some conclusion absurd, it is very difficult for us to 
appreciate the relation of this conclusion to data which are 
different and less complete ; but it is essential that we should 
realise arguments from analogy as relative to premisses, if we are 
to approach the logical theory of Induction without prejudice. 

5. While we depreciate the former probability of beliefs 
which we no longer hold, we tend, I think, to exaggerate the 
present degree of certainty of what we still believe. The preceding 
paragraph is not intended to deny that savages often greatly 

1 "This is animism, or that sense of something in Xature which to the 
enlightened or civilised man is not there, and in the civilised man's child, if it 
be admitted that he has it at all, is but a faint survival of a phase of the 
primitive mind. And by animism I do not mean the theory of a soul in 
nature, but the tendency or impulse or instinct, in which all myth originates, 
to animate all things ; the projection of ourselves into nature ; the sense and 
apprehension of an intelligence like our own, but more powerful in all visible 
. things ^ (Hudson, lar Away and Long Ago, pp, 224-5). This * tendency or 
impulse or instinct,' refined by reason and enlarged by experience, may be 
required, in the shape of an intuitive a priori probability, if some of those 
universal conclusions of common sense, which the most sceptical do not kick 
away, are to be supported with rational foundations. 


overestimate the value of their crude inductions, and are to this 
extent irrational. It is not easy to distinguish between a beliefs 
being the most reasonable of those which it is open to us to 
believe, and its being more probable than not. In the same way 
we, perhaps, put an excessive confidence in those conclusions 
the existence of other people, for instance, the law of gravity, or 
to-morrow's sunrise of which, in comparison with many other 
beliefs, we are very well assured. We may sometimes confuse 
the practical certainty, attaching to the class of beliefs upon which 
it is rational to act with the utmost confidence, with the more 
wholly objective certainty of logic. We might rashly assert, for 
instance, that to-morrow's sunrise is as likely to us as failure, 
and the special virtue of the number seven as unlikely, even to 
Pythagoras, as success, in an attempt to throw heads a hundred 
times in succession with an unbiassed coin. 1 

6. As it has often been held upon various grounds, with 
reason or without, that the validity of Induction and Analogy 
depends in some way upon the character of the actual world, 
logicians have sought for material laws upon which these methods 
can be founded. The Laws of Universal Causation and the 
Uniformity of Nature, namely, that all events have some cause 
and that the same total cause always produces the same effect, 
are those which commonly do service. But these principles 
merely assert that there are some data from which events posterior 
to them in time could be inferred. They do not seem to yield us 
much assistance in solving the inductive problem proper, or in 
determining how we can infer with probability from partial data. 
It has been suggested in the previous chapter that the Principle 
of the Uniformity of Nature amounts to an assertion that an 
argument from perfect analogy (defined as I have defined it) is 
valid when applied to events only differing in their positions in 
time or space. 2 It has also been pointed out that ordinary in- 
ductive arguments appear to be strengthened by any evidence 
which makes them approximate more closely in character to a 
perfect analogy. But this, I think, is the whole extent to which 
this principle, even if its truth could be assumed, would help us. 

1 Yet if every inhabitant of the world, Grimsehl has calculated, were to toss 
a coin every second, day and night* this latter event would only occur once on 
the average in every twenty billion years. 

1 Is this interpretation of the Principle of the Uniformity of Nature affected 
by the 3>octrine of Relativity? 


States of the universe, identical in every particular, may never 
recur, and, even if identical states were to recur, we should not 
know it. 

The kind of fundamental assumption about the character of 
material laws, on which scientists appear commonly to act, 
seems to me to be much less simple than the bare principle of 
Uniformity. They appear to assume something much more like 
what mathematicians call the principle of the superposition of 
small effects, or, as I prefer to call it, in this connection, the 
atomic character of natural law. The system of the material 
universe must consist, if this kind of assumption is warranted, 
of bodies which we may term (without any implication as to 
their size being conveyed thereby) legal atoms, such that each of 
them exercises its own separate, independent, and invariable 
effect, a change of the total state being compounded of a number 
of separate changes each of which is solely due to a separate 
portion of the preceding state. We do not have an invariable 
relation between particular bodies, but nevertheless each has on 
the others its own separate and invariable effect, which does not 
change with changing circumstances, although, of course, the 
total effect may be changed to almost any extent if all the other 
accompanying causes are different. Each atom can, accord- 
ing to this theory, be treated as a separate cause and does 
not enter into different organic combinations in each of which 
it is regulated by different laws. 

Perhaps it has not always been realised that this atomic 
uniformity is in no way implied by the principle of the 
Uniformity of Nature. Yet there might well be quite different 
laws for wholes of different degrees of complexity, and laws of 
connection between complexes which could not be stated in 
terms of laws connecting individual parts. In this case 
natural law would be organic and not, as it is generally 
supposed, atomic. If every configuration of the Universe were 
subject to a separate and independent law, or if very small 
differences between bodies in their shape or size, for instance, 
led to their obeying quite different laws, prediction would be 
impossible and the inductive method useless. Yet nature might 
still be uniform, causation sovereign, and laws timeless and 

The scientist wishes, in fact, to assume that the occurrence 


of a phenomenon which has appeared as part of a more complex 
phenomenon, may be some reason for expecting it to bo associated 
on another occasion with part of the same complex. Yet if 
different wholes were subject to different laws qua wholes and 
not simply on account of and in proportion to the differences of 
their parts, knowledge of a part could not lead, it would seem, 
even to presumptive or probable knowledge as to its association 
with other parts. Given, on the other hand, a number of legally 
atomic units and the laws connecting them, it would be possible 
to deduce their effects pro tanto without an exhaustive knowledge 
of all the coexisting circumstances. 

We do habitually assume, I think, that the size of the atomic 
unit is for mental events an individual consciousness, and for 
material events an object small in relation to our perceptions. 
These considerations do not show us a way by which we can 
justify Induction. But they help to elucidate the kind of assump- 
tions which we do actually make, and may serve as an introduction 
to what follows. 



1. THE general line of thought to be followed in this chapter may 
be indicated, briefly, at the outset. 

A system of facts or propositions, as we ordinarily conceive 
it, may comprise an indefinite number of members. But the 
ultimate constituents or indefinables of the system, which all 
the members of it are about, are less in number than these 
members themselves. Further, there are certain laws of necessary 
connection between the members, by which it is meant (I do not 
stop to consider whether more than this is meant) that the truth 
or falsity of every member can be inferred from a knowledge of 
the laws of necessary connection together with a knowledge of the 
truth or falsity of some (but not all) of the members. 

The ultimate constituents together with the laws of necessary 
connection make up what I shall term the independent variety 
of the system. The more numerous the ultimate constituents 
and the necessary laws, the greater is the system's independent 
variety. It is not necessary for my present purpose, which is 
merely to bring before the reader's mind the sort of conception 
which is in mine, that I should attempt a complete definition 
of what I mean by a system. 

Now it is characteristic of a system, as distinguished from 
a collection of heterogeneous and independent facts or proposi- 
tions, that the number of its premisses, or, in other words, the 
amount of independent variety in it, should be less than the 
number of its members. But it is not an obviously essential 
characteristic of a system that its premisses or its indepen- 
dent variety should be actually finite. We must distinguish, 
therefore, between systems which may be termed finite and 
infinite respectively, the terms finite and infinite referring not to 



the number of members in the system but to the amount of in- 
dependent variety in it. 

The purpose of the discussion, which occupies the greater 
part- of this chapter, is to maintain that, if the premisses of our 
argument permit us to assume that the facts or propositions, 
with which the argument is concerned, belong to a finite system, 
then probable knowledge can be validly obtained by means of 
an inductive argument. I now proceed to approach the question 
from a slightly different standpoint, the controlling idea, however, 
being that which is outlined above. 

2. "What is our actual course of procedure in an inductive 
argument 1 We have before us, let us suppose, a set of n in- 
stances which have r known qualities, a^ . . . a r in common, 
these r qualities constituting the known positive analogy. From 
these qualities three (say) are picked out, namely, %, a 2 , a 3 , and 
we inquire with what probability all objects having these three 
qualities have also certain other qualities which we have picked 
out, namely, <z r _ a , a r . We wish to determine, that is to say, 
whether the qualities a f _-^ a r are bound up with the qualities 
flu #23 #3- In thus approaching this question we seem to 
suppose that the qualities of an object are bound together in 
a limited number of groups, a sub-class of each group being an 
infallible symptom of the coexistence of certain other members 
of it also. 

Three possibilities are open, any of which would prove 
destructive to our generalisation. It may be the case (1) that 
a r-1 or a r is independent of all the other qualities of the instances 
they may not overlap, that is to say, with any other groups ; 
or (2) that a^a^a B do not belong to the same groups as a r ,'$> T \ 
or (3) that a^a^i^ while they belong to the same group as a^.^^, 
are not sufficient to specify this group uniquely they belong, 
that is to say, to other groups also which do not include a r-1 and 
a r . The precautions we take are directed towards reducing the 
likelihood, so far as we can, of each of these possibilities. We 
distrust the generalisation if the terms typified by # r _i# r are 
numerous and comprehensive, because this increases the likeli- 
hood that some at least of them fall under heading (1), and also 
because it increases the likelihood of (3). We trust it if the 
terms typified by a^a^a^ are numerous and comprehensive, 
because this decreases the likelihood both of (2) and of (3). If 


we find a new instance which agrees with the former instances in 
a i a 2 G 3 rf t '-i a r but not in tf 4 , we welcome it, because this disposes of 
the possibility that it is a 4 , alone or in combination, that is bound 
up with a r _!#,.. We desire to increase our knowledge of the 
properties, lest there be some positive analogy which is escaping us, 
and when our knowledge is incomplete we multiply instances, 
which we do not know to increase the negative analogy for 
certain, in the hope that they may do so. 

If we sum up the various methods of Analogy, we find, I 
think, that they are all capable of arising out of an underlying 
assumption, that if we find two sets of qualities in coexistence 
there is a finite probability that they belong to the same group, 
and a finite probability also that the first set specifies this group 
uniquely. Starting from this assumption, the object of the 
methods is to increase the finite probability and make it large. 
Whether or not anything of this sort is explicitly present to our 
minds when we reason scientifically, it seems clear to me that we 
do act exactly as we should act, if this were the assumption from 
which we set out. 

In most cases, of course, the field is greatly simplified from 
the first by the use of our pre-existing knowledge. Of the 
properties before us we generally have good reason, derived 
from prior analogies, for supposing some to belong to the same 
group and others to belong to different groups. But this does 
not affect the theoretical problem confronting us. 

3. What kind of ground could justify us in assuming the 
existence of these finite probabilities which we seem to require ? 
If we are to obtain them, not directly, but by means of argument, 
we must somehow base them upon a finite number of exhaustive 

The following line of argument seems to me to represent, on 
the whole, the kind of assumption which is obscurely present to 
our minds. We suppose, I think, that the almost innumerable 
apparent properties of any given object all arise out of a finite 
number of generator properties, which we may call <f>i$>2<f>3. - . 
Some arise out of ^ alone, some out of ^ in conjunction with < 2> 
and so on. The properties which arise out of ^ alone form one 
group ; -those which arise out of ^> 1 ^> 2 in conjunction form another 
group, and so on. Since the number of generator properties is 
finite, the number of groups also is finite. If a set of apparent 


properties arise (say) out of three generator properties 
then this set of properties may be said to specify the group 
^i^2^3- Since the total number of apparent properties is assumed 
to be greater than that of the generator properties, and since the 
number of groups is finite, it follows that, if two sets of apparent 
properties are taken, there is, in the absence of evidence to the 
contrary, a finite probability that the second set will belong 
to the group specified by the first set. 

There is, however, the possibility of a plurality of generators. 
The first set of apparent properties may specify more than one 
group, there is more than one group of generators, that is to 
say, which are competent to produce it ; and some only of these 
groups may contain the second set of properties. Let us, for 
the moment, rule out this possibility. 

When we argue from an analogy, and the instances have 
two groups of characters in common, namely <> and /, either / 
belongs to the group < or it arises out of generators partly distinct 
from those out of which < arises. For the reason already ex- 
plained there is a finite probability that / and < belong to the 
same group. If this is the case, i.e. if the generalisation g(<f>f) 
is valid, then / will certainly be true of all other cases in which 
<j> is true ; if this is not the case, then / will not always be true 
when <j> is true. We have, therefore, the preliminary conditions 
necessary for the application of puxe induction. If x r , etc., are 
the instances, 

g/Ji =2> , where j> Q is finite, 
x r /gJi=I, etc., 

and x r /x^ 2 . . , x r _}gh = I -e, where e is finite. 

And hence, by the argument of Chapter XX., the probability of a 
generalisation, based on such evidence as this, is capable, under 
suitable conditions, of tending towards certainty as a limit, when 
the number of instances is increased. 

If ^> is complex and includes a number of characters which 
are not always found together, it must include a number of 
separate generator properties and specify a large group ; hence 
tiie initial probability that / belongs to this group is relatively 
large. If, on the other hand, /is complex, there will be, for the 
same reasons mutatis mutandis, a relatively smaller initial prob- 
ability than otherwise that/ belongs to any other given group. 


When the argument is mainly by analogy, we endeavour to 
obtain evidence which, makes the initial probability p t) relatively 
high ; when the analogy is weak and the argument depends for 
its strength upon pure induction, p Q is small and p, , which is 
based upon numerous instances, depends for its magnitude upon 
their number. But an argument from induction must always 
involve some element of analogy, andi on the other hand, few 
arguments from analogy can afford to ignore altogether the 
strengthening influence of pure induction. 

4. Let us consider the manner in which the methods of 
analogy increase the initial likelihood that two characters belong 
to the same group. The numerous characters of an object which 
are known to us may be represented by a^a^ . . . a tl . We select 
two sets of these, a r and a s , and seek to determine whether a s 
always belongs to the group specified by a^ Our previous know- 
ledge will enable us, in general, to rule out many of the object's 
characters as being irrelevant to the groups specified by a r and a s9 
although this will not be possible in the most fundamental in- 
quiries. We may also know that certain characters are always 
associated with a r or with a^. But there will be left a residuum 
of whose connection with a r or a s we are ignorant. These 
characters, whose relevance is in doubt, may be represented by 
#H-I- a s-i- ^ ^ e Analogy is perfect, these characters are 
eliminated altogether. Otherwise, the argument is weakened 
in proportion to the comprehensiveness of these doubtful char- 
acters. For it may be the case that some of <z r+1 . # s _i are 
necessary as well as a r , in order to specify all the generators 
which are required to produce a s . 

5. We may possibly be justified in neglecting certain of the 
characters a r+1 &,_! by Direct judgments of irrelevance. 
There are certain properties of objects which we rule out from 
the beginning as wholly or largely independent and irrelevant to 
all, or to some, other properties. The principal judgments of 
this kind, and those alone about which we seem to feel much 
confidence, are concerned with absolute position in time and 
space, this class of judgments of irrelevance being summed up, 
I have suggested, in the Principle of the Uniformity of Nature. 
We judge that mere position in time and space cannot possibly 
affect, as a determining cause, any other characters ; and this 
belief appears so strong and certain, although it is hard to see 


how it can be based on experience, that the judgment by which 
we arrive at it seems perhaps to be direct. A further type of 
instance in which some philosophers seem to have trusted direct 
judgments of relevance in these matters arises out of the relation 
between mind and matter. They have believed that no mental 
event can possibly be a necessary condition for the occurrence of 
a material event. 

The Principle of the Uniformity of Nature, as I interpret it, 
supplies the answer, if it is correct, to the criticism that the 
instances, on which generalisations are based, are all alike in 
being past, and that any generalisation, which is applicable to 
the future, must be based, for this reason, upon imperfect analogy. 
We judge directly that the resemblance between instances, which 
consists in their being past, is in itself irrelevant, and does not 
supply a valid ground for impugning a generalisation. 

But these judgments of irrelevance are not free from difficulty, 
and we must be suspicious of using them. When I say that posi- 
tion is irrelevant, I do not mean to deny that a generalisation the 
premiss of which specifies position, may be true, and that the 
same generalisation without this limitation might be false. But 
this is because the generalisation is incompletely stated; it 
happens that objects so specified have the required characters, 
and hence their position supplies a sufficient criterion. Position 
may be relevant as a sufficient condition but never as a necessary 
condition, and the inclusion of it can only affect the truth of a 
generalisation when we have left out some other essential con- 
dition. A generalisation which is true of one instance must be 
true of another which only differs from the former by reason of 
its position in time or space. 

6. Excluding, therefore, the possibility pf a plurality of 
generators, we can justify the method of perfect analogy, and 
other inductive methods in so far as they can be made to 
approximate to this, by means of the assumption that the 
objects in the field, over which our generalisations extend, do 
not have an infinite number of independent qualities ; that, in 
oliher words, their characteristics, however numerous, cohere 
together in groups of invariable connection, which are finite 
in number. This does not limit the number of entities which 
are only numerically distinct. In the language used at the 
beginning of this chapter, the use of inductive methods can be 


justified if they are applied to what we have reason to suppose 
a finite system. 1 

7. Let us now take account of a possible plurality of 
generators. I mean by this the possibility that a given char- 
acter can arise in more than one way, can belong to more than 
one distinct group, and can arise out of more than one generator. 
$ might, for instance, be sometimes due to a generator a l3 and 
a-i might invariably produce/. But we could not generalise 
from <f> to/, if <f> might be due in other cases to a different 
generator a 2 which would not be competent to produce /. 

If we were dealing with inductive correlation, where we do 
not claim universality for our conclusions, it would be sufficient 
for us to assume that the number of distinct generators, to which 
a given property <j> can be due, is always finite. To obtain validity 
for universal generalisations it seems necessary to make the more 
comprehensive and less plausible assumption that a finite prob- 
ability always exists that there is not, in any given case, a plurality 
of causes. With this assumption we have a valid argument from 
pure induction on the same lines, nearly, as before. 

8. We have thus two distinct difficulties to deal with, and we 
require for the solution of each a separate assumption. The 
point may be illustrated by an example in which only one of the 
difficulties is present. There are few arguments from analogy of 
which we are better assured than the existence of other people. 
We feel indeed so well assured of their existence that it has been 
thought sometimes that our knowledge of them must be in some 
way direct. But analogy does not seem to me unequal to the 
proof. We have numerous experiences in our own person of 
acts which are associated with states of consciousness, and we 
infer that similar acts in others are likely to be associated with 
similar states of consciousness. But this argument from analogy 
is superior in one respect to nearly all other empirical argu- 
ments, and this superiority may possibly explain the great con- 
fidence which we feel in it. We do seem in this case to have 
direct knowledge, such as we have in no other case, that our 
states of consciousness are, sometimes at least, causally con- 
nected with some of our acts. We do not, as in other cases, 

1 Mr. C. D. Broad, in two articles " On the Relation between Induction and 
Probability" (Mind, 1918 and 1920), has been following a similar line of 



merely observe invariable sequence or coexistence between con- 
sciousness and act ; and we do believe it to be vastly improbable 
in trie case of some at least of our own physical acts that they 
could have occurred without a mental act to support them. 
Thus, we seem to have a special assurance of a kind not usually 
available for believing that there is sometimes a necessary con- 
nection between the conclusion and the condition of the 
generalisation; we doubt it only from the possibility of a 
plurality of causes. 

The objection to this argument on the ground that the analogy 
is always imperfect, in that all the observed connections of 
consciousness and act are alike in being mine, seems to me to be 
invalid on the same ground as that on which I have put on one 
side objections to future generalisations, which are based on the 
fact that the instances which support them are all alike in being 
past. If direct judgments of irrelevance are ever permissible, 
there seems some ground for admitting one here. 

9, As a logical foundation for Analogy, therefore, we seem to 
need some such assumption as that the amount of variety in the 
universe is limited in such a way that there is no one object so 
complex that its qualities fall into an infinite number of inde- 
pendent groups (i.e. groups which might exist independently 
as well as in conjunction) ; or rather that none of the objects 
about which we generalise are as complex as this ; or at least 
that, though some objects may be infinitely complex, we some- 
times have a finite probability that an object about which we 
seek to generalise is not infinitely complex. 

To meet a possible plurality of causes some further assumption 
is necessary. If we were content with Inductive Correlations 
and sought to prove merely that there was a probability in favour 
of any instance of the generalisation in question, without in- 
quiring whether there was a probability in favour of every instance, 
it would be sufficient to suppose that, while there may be more 
than one sufficient cause of a character, there is not an infinite 
number of distinct causes competent to produce it. And this 
involves no new assumption ; for if the aggregate variety of the 
system is finite, the possible plurality of causes must also be finite. 
If 9 however, our generalisation is to be universal, so that it breaks 
down if there is a single exception to it, we must obtain, by some 
means or other, a finite probability that the set of characters, 


which condition the generalisation, are not the possible effect of 
more than one distinct set of fundamental properties. I do not 
know upon what ground we could establish a finite probability 
to this effect. The necessity for this seemingly arbitrary hypo- 
thesis strongly suggests that our conclusions should be in the 
form of inductive correlations, rather than of universal general- 
isations. Perhaps our generalisations should always run : ' It is 
probable that any given < is// rather than, '' It is probable that 
all <f> are// Certainly, what we commonly seem to hold with con- 
viction is the belief that the sun will rise to-morrow, rather than 
the belief that the sun will always rise so long as the conditions 
explicitly known to us are fulfilled. This will be matter for 
further discussion in Part V,, when Inductive Correlation is 
specifically dealt with. 

10. There is a vagueness, it may be noticed, in the number of 
instances, which would be required on the above assumptions 
to establish a given numerical degree of probability, which 
corresponds to the vagueness hi the degree of probability which 
we do actually attach to inductive conclusions. We assume 
that the necessary number of instances is finite, but we do not 
know what the number is. We know that the probability of a 
well-established induction is great, but, when we are asked to 
name its degree, we cannot. Common sense tells us that some 
inductive arguments are stronger than others, and that some 
are very strong. But how much stronger or how strong we 
cannot express. The probability of an induction is only 
numerically definite when we are able to make definite assump- 
tions about the number of independent equiprobable influences 
at work. Otherwise, it is non-numerical, though bearing relations 
of greater and less to numerical probabilities according to the 
approximate limits within which our assumption as to the possible 
number of these causes lies. 

11. Up to this point I have supposed, for the sake of simplicity, 
that it is necessary to make our assumptions as to the limitation 
of independent variety in an absolute form, to assume, that is to 
say, the finiteness of the system, to which the argument is applied, 
for certain. But we need not in fact go so far as this. 

If our conclusion is C and our empirical evidence is E, then, 
in order to justify inductive methods, our premisses must include, 
in addition to E, a general hypothesis E such that C/H, the 


d priori probability of our conclusion, has a finite value. The 
effect of E is to increase the probability of C above its initial 
a priori value, C/HE being greater than C/H. But the method 
of strengthening C/H by the addition of evidence E is valid quite 
apart from the particular content of H. If, therefore, we have 
another general hypothesis E' and other evidence E', such that 
H/H' has a finite value, we can, without being guilty of a circular 
argument, use evidence E' by the same method as before to 
strengthen the probability H/H'. If we call H, namely, the 
absolute assertion of the finiteness of the system under considera- 
tion, the inductive hypothesis, and the process of strengthening 
C/H by the addition E the inductive method, it is not circular to 
use the inductive method to strengthen the inductive hypothesis 
itself, relative to some more primitive and less far-reaching assump- 
tion. If, therefore, we have any reason (H') for attributing 
d priori a finite probability to the Inductive Hypothesis (H), then 
the actual conformity of experience d posteriori with expectations 
based on the assumption of H can be utilised by the inductive 
method to attribute an enhanced value to the probability of H. 
To this extent, therefore, we can support the Inductive Hypothesis 
by experience. In dealing with any particular question we can 
take the Inductive Hypothesis, not at its d priori value, but at 
the value to which experience in general has raised it. What 
we require d priori, therefore, is not the certainty of the Inductive 
Hypothesis, but a finite probability in its favour. 1 

Our assumption, in its most limited form, then, amounts to 
this, that we have a finite d priori probability in favour of 
the Inductive Hypothesis as to there being some limitation 
of independent variety (to express shortly what I have already 
explained in detail) in the objects of our generalisation. Our 
experience might have been such as to diminish this probability 
d posteriori. It has, in fact, been such as to increase it. It is 
because there has been so much repetition and uniformity in our 
experience that we place great confidence in it. To this extent 
the popular opinion that Induction depends upon experience for 
its validity is justified and does not involve a circular argument. 

1 I have implicitly assumed in the above argument that if H' supports H, it 
strengthens an argument which H would strengthen. This is not necessarily 
the case for the reasons given on pp. 68 and 147. In these passages the 
necessary conditions for the above are elucidated. I am, therefore, assuming 
that in the case now in question these conditions actually are fulfilled- 


12, I think that this assumption is adequate to its purpose 
ajid would justify our ordinary methods of procedure in inductive 
argument. It was suggested in the previous chapter that our 
theory of Analogy ought to be as applicable to mathematical 
as to material generalisations, if it is to justify common sense. 
The above assumptions of the limitation of independent variety 
sufficiently satisfy this condition. There is nothing in these 
assumptions which gives them a peculiar reference to material 
objects. We believe, in fact, that all the properties of numbers 
can be derived from a limited number of laws, and that the same 
set of laws governs all numbers. To apply empirical methods to 
such things as numbers renders it necessary, it is true, to make 
an assumption about the nature of numbers. But it is the same 
kind of assumption as we have to make about material objects, 
and has just about as much, or as little, plausibility. There is 
no new difficulty. 

The assumption, also, that the system of Nature is finite is 
in accordance with the analysis of the underlying assumption of 
scientists, given at the close of the previous chapter. The 
hypothesis of atomic uniformity, as I have called it, while not 
formally equivalent to the hypothesis of the limitation of inde- 
pendent variety, amounts to very much the same thing. If the 
fundamental laws of connection changed altogether with varia- 
tions, for instance, in the shape or size of bodies, or if the laws 
governing the behaviour of a complex had no relation whatever 
to the laws governing the behaviour of its parts when belonging 
to other complexes, there could hardly be a limitation of inde- 
pendent variety in the sense in which this has been defined. And, 
on the other hand, a limitation of independent variety seems 
necessarily to carry with it some degree of atomic uniformity. 
The underlying conception as to the character of the System of 
Nature is in each case the same. 

13. "We have now reached the last and most difficult stage of 
the discussion. The logical part of our inquiry is complete, and 
it has left us, as it is its business to leave us, with a question of 
epistemology. Such is the premiss or assumption which our 
logical' processes need to work upon. What right have we to 
make it ? It is no sufficient answer in philosophy to plead that 
the assumption is after all a very little one. 

I do not believe that any conclusive or perfectly satisfactory 


answer to this question can be given, so long as our knowledge 
of the subject of epistemology is in so disordered and undeveloped 
a condition as it is in at present. No proper answer has yet been 
given to the inquiry of what sorts of things are we capable of 
direct knowledge ? The logician, therefore, is in a weak position, 
when he leaves his own subject and attempts to solve a particular 
instance of this general problem. He needs guidance as to what 
kind of reason we could have for such an assumption as the use 
of inductive argument appears to require. 

On the one hand, the assumption may be absolutely d priori 
in the sense that it would be equally applicable to all possible 
objects. On the other hand, it may be seen to be applicable to 
some classes of objects only. In this case it can only arise out 
of some degree of particular knowledge as to the nature of the 
objects in question, and is to this extent dependent on experience. 
But if it is experience which in this sense enables us to know the 
assumption as true of certain amongst the objects of experience, 
it must enable us to know it in some manner which we may term 
direct and not as the result of an inference. 

Now an assumption, that all systems of fact are finite (in the 
sense in which I have defined this term), cannot, it seems perfectly 
plain, be regarded as having absolute, universal validity in the 
sense that such an assumption is self-evidently applicable to every 
kind of object and to all possible experiences. It is not, therefore, 
in quite the same position as a self-evident logical axiom, and does 
not appeal to the mind in the same way. The most which can 
be maintained is that this assumption is true of some systems of 
fact, and, further, that there are some objects about which, as 
soon as we understand their nature, the mind is able to apprehend 
directly that the assumption in question is true. 

In Chapter II. 7, I wrote : " By some mental process of 
which it is difficult to give an account, we are able to pass from 
direct acquaintance with things to a knowledge of propositions 
about the things of which we have sensations or understand the 
meaning." Knowledge, so obtained, I termed direct knowledge. 
Krom a sensation of yellow and from an understanding of the 
meaning of * yellow 3 and of * colour/ we could, I suggested, 
have direct knowledge of the fact or proposition * yellow is a 
colour ; * we might also know that colour cannot exist without 
extension, or that two colours cannot be perceived at the same 


time in the same place. Other philosophers might use terms 
differently and express themselves otherwise ; but the substance 
of what I was there trying to say is not very disputable. But 
when we come to the question as to what kinds of propositions 
we can come to know in this manner, we enter upon an unex- 
plored field where no certain opinion is discoverable. 

In the case of logical terms, it seems to be generally agreed 
that if we understand their meaning we can know directly pro- 
positions about them which go far beyond a mere expression of 
this meaning ; propositions of the kind which some philo- 
sophers have termed synthetic. In the case of non-logical or 
empirical entities, it seems sometimes to be assumed that our 
direct knowledge must be confined to what may be regarded as 
an expression or description of the meaning or sensation appre- 
hended by us. If this view is correct the Inductive Hypothesis 
is not the kind of thing about which we can have direct know- 
ledge as a result of our acquaintance with objects. 

I suggest, however, that this view is incorrect, and that we 
are capable of direct knowledge about empirical entities which 
goes beyond a mere expression of our understanding or sensation 
of them. It may be useful to give the reader two examples, more 
familiar than the Inductive Hypothesis, where, as it appears to 
me, such knowledge is commonly assumed. The first is that of the 
causal irrelevance of mere position in time and space, commonly 
called the Uniformity of Nature. We do believe, and yet have 
no adequate inductive reason whatever for believing, that mere 
position in time and space cannot make any difference. This 
belief arises directly, I think, out of our acquaintance with 
the objects of experience and our understanding of the concepts 
of 'time' and ' space/ The second is that of the Law of 
Causation. We believe that every object in time ha& a f neces- 
sary ' connection 1 with some set of objects at a previous time. 
This belief also, I think, arises in the same way. It is to be 
noticed that neither of these beliefs clearly arises, in spite of the 
directness which may be claimed for them, out of any one single 
experience. In a way analogous to these, the validity of assuming 
the Inductive Hypothesis, as applied to a particular class of 
objects, appears to me to be justified. 

Our justification for using inductive methods in an argument 
1 I do not propose to define the meaning of this. 


about numbers arises out of our perceiving directly, when we 
understand the meaning of a number, that they are of the re- 
quired character. 1 And when we perceive the nature of our 
phenomenal experiences, we have a direct assurance that in their 
case also the assumption is legitimate. We are capable, that 
is to say, of direct synthetic knowledge about the nature 
of the objects of our experience. On the other hand, there 
may be some kinds of objects, about which we have no such 
assurance and to which inductive methods are not reasonably 
applicable. It may be the case that some metaphysical questions 
are of this character and that those philosophers have been right 
who have refused to apply empirical methods to them. 

14. I do not pretend that I have given any perfectly adequate 
reason for accepting the theory I have expounded, or any such 
theory. The Inductive Hypothesis stands in a peculiar position 
in that it seems to be neither a self-evident logical axiom nor an 
object of direct acquaintance ; and yet it is just as difficult, as 
though the inductive hypothesis were either of these, to remove 
from the organon of thought the inductive method which can 
only be based on it or on something like it. 

As long as the theory of knowledge is so imperfectly 
understood as now, and leaves us so uncertain about the grounds 
of many of our firmest convictions, it would be absurd to 
confess to a special scepticism about this one. I do not think 
that the foregoing argument has disclosed a reason for such 
scepticism. We need not lay aside the belief that this conviction 
gets its invincible certainty from some valid principle darkly 
present to our minds, even though it still eludes the peering 
eyes of philosophy. 

1 Since numl>ers are logical entities, it may be thought less unorthodox to 
make such an assumption in their case. 



1. THE number of books, which deal with inductive l theory, is 
extraordinarily small. It is usual to associate the subject with 
the names of Bacon, Hume, and Mill. In spite of the modern 
tendency to depreciate the first and the last of these, they are the 
principal names, I thJrtk, with which the history of induction 
ought to be associated. The next place is held by Laplace and 
Jevons. Amongst contemporary logicians there is an almost 
complete absence of constructive theory, and they content 
themselves for the most part with the easy task of criticising 
Mill, or with the more difficult one of following him. 

That the inductive theories of Bacon and of Mill are full of 
errors and even of absurdities, is, of course, a commonplace of 
criticism. But when we ignore details, it becomes clear that they 
were really attempting to disentangle the essential issues. We 
depreciate them partly, perhaps, as a reaction from the view once 
held that* they helped the progress of scientific discovery. For 
it is not plausible to suppose that Newton owed anything to Bacon, 
or Darwin to Mill. But ,with the logical problem their minds 
were truly occupied, and in the history of logical theory they 
should always be important. 

It is true, nevertheless, that the advancement of science was 
the main object which Bacon himself, though not Mill, believed 
that his philosophy would promote. The Great Insfauration was 
intended to promulgate an actual method of discovery entirely 
different from any which had been previously known. 2 It did 

1 See note at the end of this chapter on " The Use of the Term Induction" 

8 He speaks of himself as being " in hac re plane protopirus, et vestigia 

nuHius sequutus " ; and in the Praefatio Qeneralis he compares his method to 

the mariner's compass, until the discovery of which no wide sea could be 

crossed (see Spedding and Ellin, vol. i. p. 24). 



not do this, and against such pretensions Macaulay's well-known 
essay was not unjustly directed. Mill, however, ezpressly dis- 
claimed in his preface any other object than to classify and 
generalise the practices " conformed to by accurate thinkers in 
their scientific inquiries." Whereas Bacon offered rules and 
demonstrations, hitherto unknown, with which any man could 
solve all the problems of science by taking pains, Mill admitted 
that " in the existing state of the cultivation of the sciences, 
there would be a very strong presumption against any one 
who should imagine that he had effected a revolution in the 
theory of the investigation of truth, or added any fundamentally 
new process to the practice of it." 

2. The theories of both seem to me to have been injured, 
though in different degrees, by a failure to keep quite distinct 
the three objects : (1) of helping the scientist, (2) of explaining 
and analysing his practice, and (3) of justifying it. Bacon was 
really interested in the second as well as in the first, and was 
led to some of his methods by reflecting upon what distinguished 
good arguments from bad in actual investigations. To logicians 
his methods were as new as he claimed, but they had their 
origin, nevertheless, in the commonest inferences of science and 
daily life. But his main preoccupation was with the first, which 
did injury to his treatment of the third. He himself became 
aware as the work progressed that, in his anxiety to provide 
an infallible mode of discovery, he had put forth more than he 
would ever be able to justify. 1 His own mind grew doubtful, 
and the most critical parts of the description of the new method 
were never written. No one who has reflected much upon In- 
duction need find it difficult to understand the progress and 
development of Bacon's thoughts. To the philosopher who first 
distinguished some of the complexities of empirical proof in a 
generalised, and not merely a particular, form, the prospects of 
systematising these methods must have seemed extraordinarily 
hopeful. The first investigator could not have anticipated that 
Induction, in spite of its apparent certainty, would prove so 
elusive to analysis. 

Mill also was led, in a not dissimilar way, to attempt a too 

1 This view is taken in the edition of James Spedding and Leslie 
Their introductions to Bacon's philosophical works seem to me to be very greatly 
superior to the accounts to be found elsewhere. They make intelligible, what 
seems, according to other commentaries, fanciful and without sense or reason. 


simple treatment, and, in seeking for ease and certainty, to 
treat far too lightly the problem of justifying what he had 
claimed. Mill shirks, almost openly, the difficulties ; and scarcely 
attempts to disguise from himself or his readers that he grounds 
induction upon a circular argument. 

3. Some of the most characteristic errors both of Bacon and 
of Mill arise, I think, out of a misapprehension, which it has been 
a principal object of this book to correct. Both believed, without 
hesitation it seems, that induction is capable of establishing a 
conclusion which is absolutely certain, and that an argument 
is invalid if the generalisation, which it supports, admits of 
exceptions in fact. " Absolute certainty/' says Leslie Ellis, 1 " is 
one of the distinguishing characters of the Baconian induction." 
It was, in this respect, mainly that it improved upon the older 
induction per enumerationem simplicem. " The induction which 
the logicians speak of,' 5 Bacon argues in the Advancement of 
Learning, " is utterly vicious and incompetent. . . . For to con- 
clude upon an enumeration of particulars, without instance 
contradictory, is no conclusion but a conjecture." The conclusions 
of the new method, unlike those of the old, are not liable to be 
upset by further experience. In the attempt to justify these 
claims and to obtain demonstrative methods, it was necessary 
to introduce assumptions for which there was no warrant. 

Precisely similar claims were made by Mill, although there 
are passages in which he abates them, 2 for his own rules of pro- 
cedure. An induction has no validity, according to Mm as 
according to Bacon, unless it is absolutely certain. The follow- 
ing passage 3 is significant of the spirit in which the subject 
was approached by him : " Let us compare a few cases 
of incorrect inductions with others which are acknowledged 
to be legitimate. Some, we know, which were believed for 
centuries to be correct, were nevertheless incorrect. That all 
swans are white, cannot have been a good induction, since the con- 
elusion lias turned out erroneous. The experience, however, on 
which the conclusion rested was genuine." Mill has not justly 
apprehended the relativity of all inductive arguments to the 
evidence, nor the element of uncertainty which is present, more 

1 Op. cit. vol. L p. 23. 

* When he deals with Plurality of Causes, for instance. 

* Bk. ill chap. iii. 3 (the italics are mine). 


or less, in all the generalisations which they support. 1 Mill's 
methods would yield certainty, if they were correct, just as 
Bacon's would. It is the necessity, to which Mill had subjected 
himself, of obtaining certainty that occasions their want of 
reality. Bacon and Mill both assume that experiment can 
shape and analyse the evidence in a manner and to an extent 
which is not in fact possible. In. the aims and expectations with 
which they attempt to solve the inductive problem, there is on 
fundamental points an unexpectedly close resemblance beween 

4. Turning from these general criticisms to points of greater 
detail, we find liiat the line of thought pursued by Mill was 
essentially the same as that which had been pursued by Bacon, 
and, also, that the argument of the preceding chapters is, in 
spite of some real differences, a development of the same funda- 
mental ideas which underlie, as it seems to me, the theories of 
Mill and Bacon alike. 

We have seen that all empirical arguments require an initial 
probability derived from analogy, and that this initial probability 
may be raised towards certainty by means of pure induction 
or the multiplication of instances. In some arguments we depend 
mainly upon analogy, and the initial probability obtained by 
means of it (mfh the assistance, as a rule, of previous knowledge) 
is so large that numerous instances are not required. In other 
arguments pure induction predominates. As science advances 
and the body of pre-existing knowledge is increased, we depend 
increasingly upon analogy ; and only at the earlier stages of our 
investigations is it necessary to xely, for the greater part of our 
support, upon the multiplication of instances. Bacon's great 
achievement, in the history of logical theory, lay in his being the 
first logician to recognise the importance of methodical analogy 
to scientific argument and the dependence upon it of most well- 
established conclusions. The Novum Organum is mainly con- 
cerned with explaining methodical ways of increasing what I 
have termed the Positive and Negative Analogies, and of avoiding 
false Analogies. The use of exclusions and rejections, to which 

1 This misapprehension may be connected with Mill's complete failure to 
grasp with any kind of thoroughness the nature and importance of the theory of 
probability. The treatment of this topic in the System of Logic is exceedingly 
bad. His understanding of the subject was, indeed, markedly inferior to the 
best thought of his own time. 


Bacon attached supreme importance, and which he held to con- 
stitute the essential superiority of his method over those which 
preceded it, entirely consists in the determination of what char- 
acters (or natures as he would call them) belong to the positive 
and negative analogies respectively. The first two tables with 
which the investigation begins are, first, the table essentiae et 
praesentiae, which contains all known instances in which the 
given nature is present, and, second, the table declinationis sive 
absentiae in proximo, which contains instances corresponding in 
each case to those of the first table, but in which, notwithstanding 
this correspondence, the given nature is absent. 1 The doctrine 
of prerogative instances is concerned no less plainly with the 
methodical determination of Analogy. And the doctrine of 
idols is expounded for the avoidance of false analogies, standing, 
he says, in the same relation to the interpretation of Nature, as 
the doctrine of fallacies to ordinary logic. 2 Bacon's error lay 
in supposing that, because these methods were new to logic, they 
were therefore new to practice. He exaggerated also their pre- 
cision and their certainty ; and he underestimated the import- 
ance of pure induction. But there was, at bottom, nothing about 
his rules impracticable or fantastic, or indeed unusual. 

5. Almost the whole of the preceding paragraph is equally 
applicable to Mill. He agreed with Bacon in depreciating the 
part played in scientific inquiry by pure induction, and in 
emphasising the importance of analogy to all systematic investi- 
gators. But he saw further than Bacon in allowing for the 
Plurality of Causes, and in admitting that an element of pure 
induction was therefore made necessary. " The Plurality of 
Causes," he says, 3 " is the only reason why mere number of in- 
stances is of any importance in inductive inquiry. The tendency 
of unscientific inquirers is to rely too much on number, without 
analysing the instances* . . . Most people hold their conclusions 
with a degree of assurance proportioned to the mere mass of the 
experience on which they appear to rest ; not considering that 
by the addition of instances to instances, all of the same kind, 
that is, differing from one another only in points already recog- 
nised as immaterial, nothing whatever is added to the evidence of 

1 Ellis, vol. i. p. 33. 
a Ellis, voL L p. 89. 
* Book iv. chap. x. 2. 


the conclusion. A single instance eliminating some antecedent 
which existed in all the other cases, is of more value than the 
greatest multitude of instances which are reckoned by their 
number alone." Mill did not see, however, that our knowledge 
of the instances is seldom complete, and that new instances, which 
are not known to differ from the former in material respects, may 
add, nevertheless, to the negative analogy, and that the multi- 
plication of them may, for this reason, strengthen the evidence. 
It is easy to see that his methods of Agreement and Difference 
closely resemble Bacon's, and aim, like Bacon's, at the deter- 
mination of the Positive and Negative Analogies. By allowing 
for Plurality of Causes Mill advanced beyond Bacon. But he 
was pursuing the same line of thought which alike led to Bacon's 
rules and has been developed in the chapters of this book. 
Like Bacon, however, he exaggerated the precision with which 
his canons of inquiry could be used in practice. 

6. No more need be said respecting method and analysis. 
But in both writers the exposition of method is closely inter- 
mingled with attempts to justify it. There is nothing in Bacon 
which at all corresponds to Mill's appeals to Causation or to the 
Uniformity of Nature, and, when they seek for the ground of 
induction, there is much that is peculiar to each writer. It is 
my purpose, however, to consider in this place the details common 
to both, which seem to me to be important and which exemplify 
the only line of investigation which seems likely to be fruitful ; 
and I shall pursue no further, therefore, their numerous points 
of difference. 

The attempt, which I have made to justify the initial prob- 
ability which Analogy seems to supply, primarily depends upon 
a certain limitation of independent variety and upon the deriva- 
tion of all the properties of any given object from a limited 
number of primary characters. In the same way I have supposed 
that the number of primary characters which are capable of 
producing a given property is also limited. And I have argued 
that it is not easy to see how a finite probability is to be obtained 
unless we have in each case some such limitation in the number 
of the ultimate alternatives. 

It was in a manner which bears fundamental resemblances 
to this that Bacon endeavoured to demonstrate the cogency of 
his method. He considers, he says, " the simple forms or differ- 


ence of tilings which are few in number, and the degrees and 
co-ordinations whereof make all this variety." And in Valerius 
Terminus he argues "that every particular that worketh any 
effect is a thing compounded more or less of diverse single natures, 
more manifest and more obscure, and that it appeareth not to 
which of the natures the effect is to be ascribed." x It is indeed 
essential to the method of exclusions that the matter to which it 
is applied should be somehow resolvable into a finite number of 
elements. But this assumption is not peculiar, I think, to 
Bacon's method, and is involved, in some form or other, in every 
argument from Analogy. In making it Bacon was initiating, 
perhaps obscurely, the modern conception of a finite number of 
laws of nature out of the combinations of which the almost bound- 
less variety of experience ultimately arises. Bacon's error was 
double and lay in supposing, first, that these distinct elements 
lie upon the surface and consist in visible characters, and second, 
that their natures are, or easily can be, known to us, although 
the part of the Instauration, in which the manner of conceiving 
simple natures was to be explained, he never wrote. These 
beliefs falsely simplified the problem as he saw it, and led him 
to exaggerate the ease, certainty, and fruitfulness of the new 
method. But the view that it is possible to reduce all the 
phenomena of the universe to combinations of a limited number 
of simple elements which is, according to Ellis, 2 the central 
point of Bacon's whole system was a real contribution to philo- 

7. The assumption that every event can be analysed into a 
limited number of ultimate elements, is never, so far as I am 
aware, explicitly avowed by Mill. But he makes it in almost 
every chapter, and it underlies, throughout, his mode of procedure. 
His methods and arguments would fail immediately,, if we were 
to suppose that phenomena of infinite complexity, due to an 
infinite number of independent elements, were in question, or 
if an infinite plurality of causes had to be allowed for. 

In distinguishing, therefore, analogy from pure induction, 
and in justifying it by the assumption of a limited complexity in 
the problems which we investigate, I am, I think, pursuing, with 
numerous differences, the line of thought which Bacon first 

1 Quoted by Ellis, vol. L p. 41. 
Vol. i. p. 28. 


pursued and which "Mill popularised. The method of treatment 
is dissimilar, but the subject-matter and the underlying beliefs 
are, in each case, the same. 

8. Between Bacon and Mill came Hume. Hume's sceptical 
criticisms are usually associated with causality ; but argument 
by induction inference from past particulars to future generalisa- 
tions W as the real object of his attack. Hume showed, not that 
inductive methods were false, but that their validity had never 
been established and that all possible lines of proof seemed 
equally unpromising. The full force of Hume's attack and the 
nature of the difficulties which it brought to light were never 
appreciated by Mill, and he makes no adequate attempt to 
deal with them. Hume's statement of the case against induction 
has never been improved upon ; and the successive attempts 
of philosophers, led by Kant, to discover a transcendental solu- 
tion have prevented them from meeting the hostile arguments on 
their own ground and from finding a solution along lines which 
might, conceivably, have satisfied Hume himself. 

9. It would not be just here to pass by entirely the name 
of the great Leibniz, who, wiser in correspondence and frag- 
mentary projects than in completed discourses, has left to us 
sufficient indications that his private reflections on this subject 
were much in advance of his contemporaries'. He distinguished 
three degrees of conviction amongst opinions, logical certainty 
(or, as we should say, propositions known to be formally true), 
physical certainty which is only logical probability, of which a 
well-established induction, as that man is a biped, is the type, 
and physical probability (or, as we should say, an inductive 
correlation), as for example that the south is a rainy quarter. 1 
He condemned generalisations based on mere repetition of 
instances, which he declared to be without logical value, and he 
insisted on the importance of Analogy as the basis of a valid 
induction, 3 He regarded a hypothesis as more probable in 
proportion to its simplicity and its power, that is to say, to the 
number of the phenomena it would explain and the fewness of 
the assumptions it involved. In particular a power of accurate 
prediction and of explaining phenomena or experiments pre- 

1 Couturat, Opuscules et fragments inedtis de Leibniz, p. 232. 

2 Couturat, La Logique de Leibniz d'apres des documents inedits, pp. 
262, 267. 


viously untried is a just ground of secure confidence, of which 
he cites as a nearly perfect example the key to a cryptogram, 1 

10. Whewell and Jevons furnished logicians with a store- 
house of examples derived from the practice of scientists. 
Jevons, partly anticipated by Laplace, made an important 
advance when he emphasised the close relation between 
Induction and Probability. Combining insight and error, he 
spoilt brilliant suggestions by erratic and atrocious arguments. 
TTia application of Inverse Probability to the inductive problem 
is crude and fallacious, but the idea which underlies it is 
substantially good. He, too, made explicit the element of 
Analogy, which Mill, though he constantly employed it, had 
seldom called by its right name. There are few books, so 
superficial in argument yet suggesting so much truth, as Jevons's 
Principles of Science. 

11. Modern text-books on Logic all contain their chapters on 
Induction, but contribute little to the subject. Their recogni- 
tion of Mill's inadequacy renders their exposition, which, in spite 
of criticisms., is generally along his lines, nerveless and confused. 
Where Mill is clear and ofEers a solution, they, confusedly 
criticising, must withhold one. The best of them, Sigwart and 
Venn, contain criticism and discussion which is interesting, but 
constructive theory is lacking. Hitherto Hume has been master, 
only to be refuted in the mannei of Diogenes or Dr. Johnson. 

1 Letter to Coming, 19th March 1678. 



1. ISTDUCTIOX is in origin a translation of the Aristotelian 
This term was used by Aristotle in two quite distinct senses first, 
and principally, for the process by which the observation of particular 
instances, in which an abstract notion is exemplified, enables us to 
realise and comprehend the abstraction itself ; secondly, for the type 
of argument in which we generalise after the complete enumeration 
and assertion of all the particulars which the generalisation embraces. 
From this second sense it was sometimes extended to cases in which 
we generalise after an incomplete enumeration. In post- Aristotelian 
writers the induction per enumerationem simplicem approximates to 
induction in Aristotle's second sense, as the number of instances is 
increased. To Bacon, therefore, " the induction of which the logicians 
speak " meant a method of argument by multiplication of instances. 
He himself deliberately extended the use of the term so as to cover 
all the systematic processes of empirical generalisation. But he 
also used it, in a manner closely corresponding to Aristotle's first use, 
for the process of forming scientific conceptions and correct notions 
of " simple natures." 1 

2. The modern use of the term is derived from Bacon's. Mill 
defines it as "the operation of discovering and proving general 
propositions." His philosophical system required that he should 
define it as widely as this ; but the term has really been used, both 
by him and by other logicians, in a narrower sense, so as to cover 
those methods of proving general propositions, which we call empiri- 
cal, and so as to exclude generalisations, such as those of mathematics, 
which have been proved formally. Jevons was led, partly by the 
linguistic resemblance, partly because in the one case we proceed 
from the particular to the general and in the other from the general 
to the particular, to define Induction as the inverse process of 
Deduction. In contemporary logic Mill's use prevails ; but there 

1 See EUis's edition of Bacon's Works, voL L p. 37. On the first occasion 
on which Induction is mentioned in the Novum Organum, it is used in this 
secondary sense. 



is, at the same time, a suggestion arising from earlier usage, and 
because Bacon and Mill never quite freed themselves from it of 
argument by mere multiplication of instances. I have thought it 
best, therefore, to use the term pure induction to describe arguments 
which are based upon the number of instances, and to use induction 
itself for all those types of arguments which combine, in one form or 
another, pure induction with analogy. 


1. Throughout the preceding argument, as well as in Part II., 
I have been able to avoid the metaphysical difficulties which surround 
the true meaning of cause. It was not necessary that I should 
inquire whether I meant by causal connection an invariable con- 
nection in fact merely, or whether some more intimate relation was 
involved. It has also been convenient to speak of causal relations 
between objects which do not strictly stand in the position of cause 
and effect, and even to speak of a probable cause, where there is no 
implication of necessity and where the antecedents will sometimes 
lead to particular consequents and sometimes will not. In making 
this use of the term, I have followed a practice not uncommon amongst 
writers on probability, who constantly use the term cause, where 
hypothesis might seem more appropriate. 1 

One is led, almost inevitably, to use e cause ' more widely than 
6 sufficient cause * or than 6 necessary cause,' because, the necessary 
causation of particulars by particulars being rarely apparent to us, 
the strict sense of the term has little utility. Those antecedent 
circumstances, which we are usually content to accept as causes, are 
only so in strictness under a favourable conjunction of innumerable 
other influences. 

2. As our knowledge is partial, there is constantly, in our use 
of the term cause, some reference implied or expressed to a limited 
body of knowledge. It is clear that, whether or not, as Cournot 2 
maintains, there are such things as independent series in the order 
of causation, there is often a sense in which we may hold that there 
is a closer intimacy between some series than between others. This 
intimacy is relative, I think, to particular information, which is 
actually known to us, or which is within our reach. It will be useful, 
therefore, to give precise definitions of these wider senses in which 
it is often convenient to use the expression cause. 

1 Of. Czuber, WaJirscheMichkeiterechnung, p. 139. In dealing with Inverse 
Probability Czuber explains that lie means by possible cause the various Be- 
dingungskoniplexe from which the cause can result. 

* See Chapter XXIV. 3. 


We must first distinguish between assertions of law and assertions 
of fact, or, in the terminology of Von Kries, 1 between nomologic and 
ontologic knowledge. It may be convenient; in dealing with some 
questions to frame this distinction with reference to the special 
circumstances. But the distinction generally applicable is between 
propositions which contain no reference to particular moments of 
time, and existential propositions which cannot be stated without 
reference to specific points in the time series. The Principle of the 
Uniformity of Nature amounts to the assertion that natural laws 
are all, in this sense, timeless. We may, therefore, divide our data 
into two portions k and Z, such that k denotes our formal and 
nomologic evidence, consisting of propositions whose predication 
does not involve a particular time reference, and I denotes the 
existential or ontologic propositions. 

3. Let us now suppose that we are investigating two existential 
propositions a and b, which refer two events A and B to particular 
moments of time, and that A is referred to moments which are all 
prior to those at which B occurred. What various meanings can we 
give to the assertion that A and B are causally connected ? 

(i.) If bjak - 1, A is a sufficient cause of B. In this case A is a 
cause of B in the strictest sense, "b can be inferred from a, and no 
additional knowledge consistent with k can invalidate this. 

(ii.) If b/dk = 0, A is a necessary cause of B. 

(iii.) If k includes all the laws of the existent universe, then A 
is not a sufficient cause of B unless b/ak = 1. The Law of Causation, 
therefore, which states that every existent has to some other previous 
existent the relation of effect to sufficient cause, is equivalent to the 
proposition that, if k is the body of natural law, then, if 6 is true, 
there is always another true proposition a, which asserts existences 
prior to B, such that bfak = l. No use has been made so far of our 
existential knowledge I, which is irrelevant to the definitions pre- 

(iv.) If b(aJd = 1 and b/kl 4= 1, A is a sufficient cause of B under 
conditions L 

(v.) If b/akl = and bjU * 0, A is a necessary cause of B under 
conditions I. 

(vi.) If there is any existential proposition h such that b/ahk = 1 
and b/hk * 1, A is, relative to k, a possible sufficient cause of B. 

(viL) If there is an existential proposition h such that b/dhk = 
and bjhk * 0, A is, relative to k, a possible necessary cause of B. 

(viiL) If b/ahU = 1 3 b/hk 4= 1, and h/akl =*= 0, A is, relative to k, 
a possible sufficient cause of B under conditions I. 

(ix.) If bfaffl^Q, b/hE*Q, h/akl *0, and hfakl*Q, A is, 
relative to A, a possible necessary cause of B under conditions Z. 

1 Die Prindpien der WahrscheiTdichkeiterecTinung, p. 86. 


Thus an event is a possible necessary cause of another, relative to 
given nomologic data, if circumstances can arise, not inconsistent 
with our existential data, in which the first event will be indispensable 
if the second is to occur. 

(x.) Two events are causally independent if no part of either is. 
relative to our nomologic data, a possible cause of any part of the 
other under the conditions of our existential knowledge. The greater 
the scope of our existential knowledge, the greater is the likelihood 
of our being able to pronounce events causally dependent or inde- 

4. These definitions preserve the distinction between c causally 
independent* and 'independent for probability/ the distinction 
between causa essendi and causa cognoscendi. If b/ahJcl^l/dlikl, 
where a and 6 may be any propositions whatever and are not limited 
as they were in the causal definitions, we have c dependence for 
probability/ and a is a causa cognoscendi for 6, relative to data Id. 
If a and 6 are causally dependent, according to definition (x.) 3 & is a 
possible causa essendi, relative to data Id* 

But, after all, the essential relation is that of * independence for 
probability.' We wish to know whether knowledge of one fact 
throws light of any kind upon the likelihood of another. The theory 
of causality is only important because it is thought that by means of 
its assumptions light can be thrown by the experience of one pheno- 
menon upon the expectation of another. 






1. MANY important differences of opinion in the treatment of 
Probability have been due to confusion or vagueness as to 
what is meant by Randomness and by Objective Chance, as 
distinguished from what, for the purposes of this chapter, may be 
termed Subjective Probability. It is agreed that there is a sort 
of Probability which depends upon knowledge and ignorance, and 
is relative, in some manner, to the -mind of the subject ; but it is 
supposed that there is also a more objective Probability which 
is not thus dependent, or less completely so, though precisely 
what this conception stands for is not plain. The relation of 
Randomness to the other concepts is also obscure. The problem 
of clearing up these distinctions is of importance if we are to 
criticise certain schools of opinion intelligently, as well as to the 
treatment of the foundations of Statistical Inference which is to 
be attempted in Part V. 

There are at least three distinct issues to be kept apart. There 
is the antithesis between knowledge and ignorance, between 
events, that is to say, which we have some reason to expect, and 
events which we have no reason to expect, which gives rise to 
the theory of subjective probability and subjective chance ; and, 
connected with this, the distinction between ' random * selection 
and c biassed * selection. There are next objective probability and 
objective chance, which are as yet obscure, but which are com- 
monly held to arise out of the antithesis between c cause ' and 
e chance/ between events, that is to say, which are causally con- 
nected and events which are not causally connected. And there 
is, lastly, the antithesis between chance and design, between 
* blind causes * and * final causes,' where we oppose a * chance ' 



event to one, part of whose cause is a volition following on a 
conscious desire for the event. 1 

2. The method of this treatise has been to regard subjective 
probability as fundamental and to treat all other relevant con- 
ceptions as derivative from this. That there is such a thing as 
probability in this sense has been admitted by all sensible philo- 
sophers since the middle of the eighteenth century at least. 2 But 
there is also, many writers have supposed, something else which 
may be fitly described as objective probability; and there is, 
besides, a long tradition in favour of the view that it is this (what- 
ever it may be) which is logically and philosophically important, 
subjective probability being a vague and mainly psychological 
conception about which there is very little to be said. 

The distinction exists already in Hume : " Probability is of 
two kinds, either when the object is really in itself uncertain, 
and to be determined by chance ; or when, though the object be 
already certain, yet 'tis uncertain to our judgment, which finds 
a number of proofs on each side of the question." 3 But the 
distinction is not elucidated, and one can only infer from other 
passages that Hume did not intend to imply in this passage the 
existence of objective chance in a sense contradictory to a deter- 
minist theory of the Universe. In Condorcet all is confused ; and 
in Laplace nearly all. In the nineteenth century the distinction 
begins to grow explicit in the writings of Cournot. " Les explica- 
tions que j'ai donn&s . . . ," he writes in the preface to his 
Exposition, "sur le double sens du mot de probability qui 
tantot se rapporte a une certaine mesure de nos connaissances, et 
tantfit a une mesure de la possibility des choses, independam ment 
de la connaissance que nous en avons : ces explications, dis-je, 
me semblent propres a resoudre les difficultes qui ont rendu 
jusqu'ici suspecte a de bons esprits toute la th6orie de la proba- 
bilite mathematique." It will be worth while to pause for a 
moment to consider the ideas of Cournot. 

1 This is discussed in Chapter XXV. 4. 

8 D'Alembert, collecting (largely from Hume, many passages being trans- 
lated almost verbatim) in the Encyclopdie m&hodicpie, the most up-to-date 
commonplaces of the subject, found it natural to write : "II n'y a point de 
hasard a proprement parler ; mais il y a son equivalent : 1'ignorance, oft nons 
sommes des vraies causes des eVenemens, a sur notre esprit 1'influence qu*on 
suppose au hasard." Compare also the sentences from Spinoza quoted on 
p. 117 above. 

* A Treatise of Human Nature, Book ii. part iii section ix. - 


3. Cournot, while admitting that there is such a thing as sub- 
jective chance, was concerned to dispute the opinion that chance 
is merely the offspring of ignorance, saying that in this case 
" le caleul des chances " is merely " un caleul des illusions." 
The chance, upon which " le ealcul des chances " is based, is 
something different, and depends, according to him, on the com- 
bination or convergence of phenomena belonging to independent 
series. By " independent series " he means series of phenomena 
which develop as parallel or successive series without any causal 
interdependence or link of solidarity whatever. 1 No one, he 
says by way of example, seriously believes that in striking the 
ground with his foot he puts out the navigator in the Antipodes, 
or disturbs the system of Jupiter's satellites. Separate trains of 
events, that is to say, have been set going by distinct initial acts of 
creation, so to speak. 2 Every event is causally connected with 
previous events belonging to its own series, but it cannot be 
modified by contact with events belonging to a different series. 
A c chance * event is a complex due to the concurrence in time 
or place of events belonging to causally independent series. 

This theory, as it stands, is evidently unsatisfactory. Even 
if there are series of phenomena which are independent in Cournot's 
sense, it is not clear how we can know which they are, or how we 
can set up a calculus which presumes an acquaintance with them. 
Just as it is likely that we are all cousins if we go back far enough, 
so there may be, after all, remote relationships between ourselves 
and Jupiter. A remote connection or a reaction quantitatively 
small is a matter of degree and not by any means the same thing 
as absolute independence. Nevertheless Cournot has contri- 
buted something, I think, to the stock of our ideas. He has 

1 "' Le mot hasard," Cournot writes in his Essai sur Us fondem&nts de nos 
connaissances, " n'indique pas une cause substantielle, mais une idee : cette idee 
est celle de la combinaison entre plusieurs series de causes ou de faits qui se 
deVeloppent chacun dans sa serie propre, independamment les uns des autoes." 
This is very like the definition given bj Jean de la Placette in his Traite desjeux 
de hasard, to which Cournot refers : " Pour moi, je suis persuade que le hasard 
renferme quelque chose de real et de positif, savoir on coneours de deux ou 
plusieurs evenements contingents, chacun desquels a ses causes, mais en sorte 
que leur coneours n'en a aucune que Ton connaisse." 

3 Essai sur les fondements de nos connaissances, L 134 : " La nature ne se 
gouverne pas par une loi unique ... ses lois ne sont pas toutes derivees les 
unes des autres, ou"derivees toutes d'une loi superieure par une necessite pure- 
ment logique . . . nous devons les eoncevoir an contraire comme ayant pu 
&tre decretees separement d'une infinite de manieres." 


hinted at, even if he has not disentangled, one of the elements 
in a common conception of chance ; and of the notion, which he 
seems to have in his mind, we must in due course take account. 1 

4. In the writings of Condorcet, I have said above, all is con- 
fused. But in Bertrand's criticism of him a relevant distinction, 
though not elucidated, is brought before the mind. " The 
motives for believing," wrote Condorcet, " that, from ten million 
white balls mixed with one black, it will not be the black ball 
which I shall draw at the first attempt is of the same kind as the 
motive for believing that the sun will not fail to rise to-morrow." 
" The assimilation of the two cases," Bertrand writes in criticism 
of the above, 2 " is not legitimate : one of the probabilities is 
objective, the other subjective. The probability of drawing 
the black ball at the first attempt is 1Q>0 oo,ooo ne ^ er more nor 
less. Whoever evaluates it otherwise makes a mistake. The 
probability that the sun will rise varies from one mind to another. 
A scientist might hold on the basis of a false theory, without being 
utterly irrational, that the sun will soon be extinguished ; he 
would be within his rights, just as Condorcet is within his ; both 
would exceed their rights in accusing of error those who think 
differently." Before commenting on this distinction, let us have 
before us also some interesting passages by Poincare. 

5. We certainly do not use the term e chance/ Poincare points 
out, as the ancients used it, in opposition to determinism. For 
us therefore the natural interpretation of * chance ' is subjective, 
" Chance is only the measure of our ignorance. Fortuitous 
phenomena are, by definition, those, of the laws of which we are 

1 Cournot's work oil Probability has been highly praised by authorities as 
diverse and distinguished as Boole and Von Kries, and has been made the 
foundation of a school by some recent French philosophers (see the special 
number of the Revue de metaphysique el de morale, devoted to Cournot and pub- 
lished in 1905, and the bibliography at the end of the present volume passim). 
The best account with which. I am acquainted, of Cournot's theory of probability, 
is to be found in A. Darbon's Le Concept du Tiasard. Cournot's philosophy of 
the subject is developed, not so much in his Exposition de la theorie des chances, 
as in later works, especially in his Essai sur les fondements de nos connaissances. 
Cournot never touched any subject without contributing something to it, but, 
on the whole, his work on Probability is, in my opinion, disappointing. K^o 
doubt his Exposition is superior to other French text-books of the period, of 
which there is so large a variety, and his work, both here and elsewhere, is not 
without illuminating ideas : but the philosophical treatment is so confused and 
indefinite that it is difficult to make {much of it beyond the one specific point 
treated above. 

* Oalcul des probabilitis, p. xix. 


ignorant." But Poincare immediately adds : " Is this definition 
very satisfactory ? When the first Chaldaean shepherds followed 
with their eyes the movements of the stars, they did not yet 
know the laws of astronomy, but would they have dreamed of 
saying that the stars move by chance ? If a modern physicist 
is studying a new phenomenon, and if he discovers its law on 
Tuesday, would he have said on Monday that the phenomenon 
was fortuitous ? " x 

There is also another type of case in which " chance must be 
something more than the name we give to our ignorance/* Among 
the phenomena, of the causes of which we are ignorant, there are 
some, such as those dealt with by the manager of a life insurance 
company, about which the calculus of probabilities can give real 
information. Surely it cannot be thanks to our ignorance, 
Poincare urges, that we are able to arrive at valuable conclusions. 
If it were, it would be necessary to answer an inquirer thus : 
" You ask me to predict the phenomena that will be produced. 
If I had the misfortune to know the laws of these phenomena, I 
could not succeed except by inextricable calculations, and I should 
have to give up the attempt to answer you ; but since I am 
fortunate enough to be ignorant of them, I will give you an answer 
at once. And, what is more extraordinary still, my answer will 
be right." The ignorance of the manager of the life insurance 
company as to the prospects of life of his individual policy- 
holders does not prevent his being able to pay dividends to his 

Both these distinctions seem to be real ones, and Poincare* 
proceeds to examine further instances in which we seem to 
distinguish objectively between events according as they are or 
are not due to ( chance/ He takes the case of a cone balanced 
upon its tip ; we know for certain that it will fall, but not on 
which side chance will determine. " A very small cause which 
escapes our notice determines a considerable effect that we cannot 
fail to see, and then we say that that effect is due to chance/' 
The weather, and the distribution of the minor planets on the 
Zodiac, are analogous instances. And what we term * games of 
chance ' afford, it has always been recognised, an almost perfect 

1 Calcul des probability (2nd edition), p. 2. This passage also appears in an 
article in the Revue du mois for 1907 and in the author's Science et mefhode, of 
the English translation of which I have made use above, at the cost of doing 
incomplete justice to Poincare^s most admirable style. 


example. " It may happen that small differences in the initial 
conditions produce very great ones in the final phenomena. A 
small error in the former will produce an enormous error in the 
latter. Prediction becomes impossible, and we have the fortuit- 
ous phenomenon." " The greatest chance is the birth of a great 
man. It is only by chance that the meeting occurs of two genital 
cells of different sex that contain precisely, each on its side, the 
mysterious elements, the mutual reaction of which is destined 
to produce genius. . . . How little it would have taken to make 
the spermatozoid which carried them deviate from its course. 
It would have been enough to deflect it a hundredth part of an 
inch, and Napoleon would not have been born and the destinies 
of a continent changed. No example can give a better compre- 
hension of the true character of chance." 

Poincar6 calls attention next to another class of events, which 
we commonly assign to ' chance/ the distinguish ing characteristic 
of which seems to be that their causes are very numerous and 
complex, the motions of molecules of gas, the distribution of 
drops of rain, the shuffling of a pack of cards, or the errors of 
observation. Thirdly there is the type, usually connected with 
one of the first two, and specially emphasised, as we have seen 
above, by Cournot, in which something comes about through 
the concurrence of events which we regard as belonging to distinct 
causal trains, a man is walking along the street and is killed by 
the fall of a tile. 

6. When we attribute such events, as those illustrated by 
Poincare, to chance, we certainly do not mean merely to assert 
that we do not know how they arose or that we had no special 
reason for anticipating them d priori. So far from this being the 
case, we mean to make a definite assertion as to the kind of way 
in which they arose ; though exactly what we mean to assert 
about them it is extremely difficult to say. 

Now a careful examination of all the cases in which various 
writers claim to detect the presence of c objective chance ' con- 
firms the view that ' subjective chance/ which is concerned with 
knowledge and ignorance, is fundamental, and that so-called 
'objective chance/ however important it may turn out to be 
from the practical or scientific point of view, is really a special 
kind of * subjective chance ' and a derivative type of the latter. 
For none of the adherents of * objective chance * wish to question 


the determinist character of natural order ; and the possibility 
of this objective chance of theirs seems always to depend on the 
possibility that a particular kind of knowledge either is ours or 
is within our powers and capacity. Let me try to distinguish as 
exactly as I can the criterion of objective chance. 

7. When we say that an event has happened by chance, we 
do not mean that previous to its occurrence the event was, on 
the available evidence, very improbable ; this may or may not 
have been the case. We say, for example, that if a coin falls heads 
it is * by chance/ whereas its falling heads is not at all improbable. 
The term 6 by chance ' has reference rather to the state of our 
information about the concurrence of the event considered and 
the event premised. The fall of the coin is a chance event if 
our knowledge of the circumstances of the throw is irrelevant 
to our expectation of the possible alternative results. If the 
number of alternatives is very large, then the occurrence of 
the event is not only subject to chance but is also very im- 
probable. In general two events may be said to have a chance 
connection, in the subjective sense, when knowledge of the 
first is irrelevant to our expectation of the second, and produces 
no additional presumption for or against it ; when, that is to 
say, the probabilities of the propositions asserting them are 
independent in the sense defined in Chapter XII. 8. 

The above definition deals with chance in the widest sense. 
What is the differentia of the narrower group of cases to which 
it is desired to apply the term * objective chance * ? The occur- 
rence of an event may be said to be subject to objective chance, 
I think, when it is not only a chance event in the above sense, 
but when we also have good reason to suppose that the addition 
of further knowledge of a given kind, if it were procurable, would 
not affect its chance character. We must consider, that is to say, 
the probability which is relative not to actual knowledge but to 
the whole of a certain kind of knowledge. We may be able to 
infer from our evidence that, even with certain kinds of 
additions to our knowledge, the connections between the events 
would still be subject to chance in the sense just defined, and 
we may be able to infer this without actually having the addi- 
tional information in question. If, however complete our 
knowledge of certain kinds of things might be, there would still 
exist independence between the propositions, the conjunction 


of which we are investigating, then we may say there is an 
objective sense in which the actual conjunction of these pro- 
positions is due to chance. 

8. This is, I think, the right line of inquiry. It remains to 
decide, what kinds of information must be irrelevant to the 
connection, in order that the presence of objective chance may 
be established. 

When we attribute a coincidence to objective chance, we 
mean not only that we do not actually know a law of connection, 
but, speaking roughly, that there is no law of connection to be 
known. And when we say that the occurrence of one alterna- 
tive rather than another is due to chance, we mean not only 
that we know no principle by which to choose between the 
alternatives, but also that no such principle is knowable. This 
use of the term closely corresponds to what Venn means by the 
term c casual ' : " We call a coincidence casual, I apprehend, 
when we mean to imply that no knowledge of one of the two 
elements, which we can suppose to be practically attainable, 
would enable us to expect the other." 1 

To make this more precise, we must revive our distinc- 
tion, 2 between nomologic knowledge and ontologic knowledge, 
between knowledge of laws and knowledge of facts or existence. 
Given certain facts f(a) about a and certain laws of connection, L, 
we can infer certainly or probably other facts (f>(a) about a. If 
a complete knowledge of laws of connection together with /(a) 
yields no appreciable probability for preferring <f>(a) to other 
alternatives, then I suggest that an actual connection between $ 
and/ in a particular instance may be said to be due to chance in 
a sense which usage justifies us in calling objective. We do 
not, in fact, when we speak of objective chance, always use it 
in so strict a sense as this, but this is, I think, the underlying 
conception to which current usage approximates. Current 
usage diverges from this sense mainly for two reasons. We 
speak of objective chance if in the above conditions our 
grounds for preference, though appreciable, are very small ; and 
we are not insistent to assert the rule of chance if a comparatively 
slight addition to our ontologic knowledge would render the 
probability or the grounds for preference appreciable. 

1 Logic of Chance, p. 245. 
* See Part III. Note (ii.) 2, p. 275. 

a. xxrv 


To sum up the above, an event is due to objective chance if 
in order to predict it, or to prefer it to alternatives, at present 
equi-probable, with any high degree of probability, it would be 
necessary to know a great many more facts of existence about 
it than we actually do know, and if the addition of a wide 
knowledge of general principles would be little use. 

It must be added that we make a distinction between facts of 
existence which are highly variable from case to case and those 
which are constant or nearly constant over a certain field of 
observation or experience. Within the limits of this field we 
regard the per-manent facts of existence as being, from the stand- 
point of chance, in nearly the same position as laws. A connec- 
tion is not due to chance, therefore, if a knowledge of the per- 
manent facts of existence could lead to their prediction. 

To sum up again therefore, if within a given field of observa- 
tion or experience a knowledge of those facts of existence which are 
permanent or invariable within that field, together with a know- 
ledge of all the relevant fundamental causal laws or general 
principles, and of a few other facts of existence, would not 
permit us, given/(a), to attribute an appreciable probability to 
<f>(a) (or an appreciable probability to the alternative <pi(a) 
rather than < 2 ( a )) I *ken the conjunction of <(a) (or of ^(a) 
rather than $ 2 ( a ) with /(a)) is due to objective chance. 

9. If we return to the examples of ^Poincare", the above defini- 
tion appears to conform satisfactorily with the usages of common 
sense. It is when an exact knowledge of fact, as distinguished 
from principle, is required for even approximate prediction that 
the expression ' objective chance ? seems applicable. But 
neither our definition nor usage is precise as to the amount of 
knowledge of fact which must be required for prediction, in 
order that, in the absence of it, the event may be regarded as 
subject to objective chance. 

It may be added that the expression e chance * can be used 
with reference to general statements as well as to particular facts. 
We say, for example, that it is a matter of chance if a man dies 
on his birthday, meaning that, as a general principle and in the 
absence of special information bearing on a particular case, there 
is no presumption whatever in favour of his dying on his birthday 
rather than on any other day. If as a general rule there were cele- 
brations on such a day such as would be not unlikely to accelerate 



death, we should say that a man's dying on his birthday was not 
altogether a matter of chance. If we knew no such general rule 
but did not know enough about birthdays to be assured that there 
was no such rule, we could not call the chance e objective ' ; we 
could only speak of it thus, if on the evidence before us there was a 
strong presumption against the existence of any such general rule. 

10. The philosophical and scientific importance of objective 
chance as defined above cannot be made plain, until Part V., on 
the Foundations of Statistical Inference, has been reached. There 
it will appear in more than one connection, but chiefly in connec- 
tion with the application of Bernoulli's formula. In cases where 
the use of this formula is valid, important inferences can be drawn; 
and it will be shown that, when the conditions for objective chance 
are approximately satisfied, it is probable that the conditions 
for the application of Bernoulli's formula will be approximately 
satisfied also. 

11, The term random has been used, it is well recognised, in 
several distinct senses. Venn 1 and other adherents of the 
* frequency * theory have given to it a precise meaning, but one 
which has avowedly very little relation to popular usage. A 
random sample, says Peirce, 2 is one " taken according to a precept 
or method, which, being applied over and over again indefinitely, 
would in the long run result in the drawing of any one set of in- 
stances as often as any other set of the same number," The 
same fundamental idea has been expressed with greater precision 
by Professor Edgeworth in connection with his investigations 
into the law of error. 8 It is a fatal objection, in my opinion, to 
this mode of defining randomness, that in general we can only 
know whether or not we have a random sample when our know- 
ledge is nearly complete. Its divergence from ordinary usage is 
well illustrated by the fact that there would be perfect randomness 
in the distribution of stars in the heavens, as Venn explicitly points 
out, if they were disposed in an exact and symmetrical pattern. 4 

1 Logic of Chance, chap, v., " The Conception Randomness and its Scientific 

* " A Theory of Probable Inference " (published in Johns Hopkins Studies in 
Logic}, p. 152, 

3 Law of Error," Gamb. PhiL Trans., 1904, p. 128. 

4 But it may be added that this seems inconsistent with Venn's conception 
of randomness as that of aggregate order and individual irregularity ; nor is it 
concordant with Venn's typically random diagram (p. 118). HJS usage, there- 
fore, is sometimes nearer than his definition to the popular usage. 


I do not believe, therefore, that this kind of definition is a 
useful one. The term must be defined with reference to prob- 
ability, not to what will happen " in the long run " ; though 
there may be two senses of it, corresponding to subjective and 
objective probability respectively. 

The most important phrase in which the term is used is that 
of ' a random selection ' or ' taken at random/ When we apply 
this term to a particular member of a series or collection of 
objects, we may mean one of two things. We may mean that 
our knowledge of the method of choosing the particular member 
is such that d priori the member chosen is as likely to be any 
one member of the series as any other. We may also mean, 
not that we have no knowledge as to which particular member 
is in question, but that such knowledge as we have respecting 
the particular member, as distinguished from other members of 
the series, is irrelevant to the question as to whether or not 
this member has the characteristic under examination. In the 
first case the particular member is a random member of the 
series for all characteristics ; in the second case it is a random 
member for some only. As the second case is the more general, 
we had better take that for the purpose of defining 'random 
selection. 9 

The point will be brought out further if we discuss the 
more difficult use of the term. What exactly do we mean by 
the statement : " Any number, taken at random, is equally 
likely to be odd or even " ? According to the frequency theory, 
this simply means that there are as many odd numbers as there 
are even. Taking it in a sense corresponding to subjective 
chance (and to the explanations given above), I propose as 
a definition the following : a is taken at random from the 
class S for the purposes of the prepositional function S(o?) . <f>(x) 9 
relative to evidence h, if * x is a 9 is irrelevant to the probability 
<(oj)/S(a?) . Ji. Thus * the number of the inhabitants of Trance is 
odd * is, relative to my knowledge, a random instance of the 
propositional function e x is an odd number/ since * a is the 
number of the inhabitants of France * is irrelevant to the prob- 
ability of ' a is odd/ * Thus to say that a number taken at 
random is as likely to be odd as even, means that there is a 

1 la the above S(a;) stands for * x is a number,' (f>(x) stands for * # is odd,' 
a stands for ' the number of inhabitants of France.' 


probability | that any instance taken at random of the 
generalisation * all numbers are odd ' (or of the corresponding 
generalisation c all numbers are even ') is true ; an instance being 
taken at random in respect of evenness or oddness, if our 
knowledge about it satisfies the conditions defined above. 
Whether or not a given instance is taken at random, depends, 
therefore, upon what generalisation is in question. 

12. We may or may not have reason to believe that, if we take 
a series of random selections, the proportionate number of 
occurrences of one particular type of result will very probably 
lie within certain limits. For reasons to be explained in Chapter 
XXIX. 9 random selection relative to such information may 
conveniently be termed 'random selection under Bernoullian 
conditions.' It is this kind of random selection which is scientific- 
ally and statistically important. But, as this corresponds to 
' objective chance/ it is convenient to have a wider definition 
of * random selection " unqualified, corresponding to tf subjective 
chance * ; and it is this wider definition which is given above. 

The term opposite to * random selection * in ordinary usage 
is * biassed selection/ When I use this phrase without qualifica- 
tion I shall use it as the opposite of ' random selection ' in the 
wider unqualified sense. 



1. THERE are two classical problems in which attempts have been 
made to attribute certain astronomical phenomena to a specific 
cause, rather than to objective chance in some such sense as has 
been defined in the preceding chapter. 

The first of these is concerned with the inclinations to the 
ecliptic of the orbits of the planets of the solar system. This 
problem has a long history, but it will be sufficient to take De 
Morgan's statement of it. 1 If we suppose that each of the orbits 
might have any inclination, we obtain a vast number of combina- 
tions of which only a small number are such that their sum is as 
small or smaller than the sum of those of the actual system. 
But the very existence of ourselves and oux world can be shown 
to imply that one of this small number has been selected, and 
De Morgan derives from this an enormous presumption that 
" there was a necessary cause in the formation of the solar system 
for the inclinations being what they are." 

The answer to this was pointed out by D'Alembert 2 in criticis- 

1 Article on Probabilities in Encyclopaedia Metropolitans, p. 412, 46. Be 
Morgan takes this without acknowledgment from Laplace, Theorie analytique 
des probabilites (1st edition), pp. 257, 258. Laplace also allows for the fact 
that all the planets move in the same sense as the earth. He concludes : "On 
verra que 1'existence d'une cause commune qui a dinge" tous ces mouvemens 
dans le sens de la rotation du soleil, et sur des plans peu inclines a celui de son 
e"quateur, est indiqu6e avec une probabiHte bien superieure a celle du plus 
grand nombre des faits historiques sur lesquels on ne se pennet aucun doute." 
Laplace had in Ms turn borrowed the example, also without acknowledgment, 
from Daniel Bernoulli. See also D'Alembert, Opuscules mathematiques, vol. iv., 
1768, pp. 89 and 292. 

2 Op. cit. p. 292. " H y a certainement d'infini centre un a parier que les 
Plandtes ne devraient pas se trouver dans le m$me plan ; ce n'est pas une raison 
pour en conclure que cette disposition, si elle avoit lieu, auroit necessairement 
d'autre cause que le hasard ; car il y auroit de m6me 1'infini centre un & parier 


ing Daniel Bernoulli. De Morgan could liave reached a similar 
result whatever the configuration might have happened to be. 
Any arbitrary disposition over the celestial sphere is vastly 
improbable d priori, that is to say in the absence of known laws 
tending to favour particular arrangements. It does not follow 
from this, as De Morgan argues, that any actual disposition 
possesses d posteriori a peculiar significance. 

2. The second of these problems is known as Michell's problem 
of binary stars, Michell's Memoir was published in the Philo- 
sophical Transactions for 1767. 1 It deals with the question as to 
whether stars which are optically double, i.e. which are so situated 
as to appear close together to an observer on the earth are also 
physically so " either by an original act of the Creator, or in con- 
sequence of some general law, such perhaps as gravity." He 
argues that if the stars " were scattered by mere chance as it 
might happen ... it is manifest . . . that every star being 
as likely to be in any one situation as another, the probability that 
any one particular star should happen to be within a certain 
distance (as, for example, one degree) of any other given star 
would be represented ... by a fraction whose numerator would 
be to its denominator as a circle of one degree radius to a circle 
whose radius is the diameter of a great circle . . . that is, about 
1 in 13131." Erom this beginning he derives an immense pre- 
sumption against the scattering of the several contiguous stars 
that may be observed " by mere chance as it might happen." 
And he goes on to argue that, if there are causal laws directly 
tending to produce the observed proximities, we may reasonably 
suppose that the proximities are actual, and not merely optical 
and apparent. The fact that Michell's induction was confirmed 
by the later investigations of Herschefl adds interest to the 
speculation. But apart from this the argument is evidently 

que les Planetes pourroient n'avoir pas une certaine disposition d6termine & 
volonte. . . ." 

D'Alembert is employing the instance for his otm purposes, in order to build 
up an ad homiTtem argument in favour of his theory concerning * runs ' against 
D. Bernoulli (see also p. 317). 

1 See also Todhimter's History, pp. 332-4 ; Venn, Logic of Ghance, p. 260 ; 
Forbes, " On the Alleged Evidence for a Physical Connexion between Stars 
forming Binary or Multiple Groups, deduced from the Doctrine of Chances," 
Phil. Mag., 1850, and Boole, " On the Theory of Probabilities and in par- 
ticular on Michell's Problem of the Distribution of the Mxed Stars," Phil. 
Mag., 1851. 


subtler than in the first example. Michell argues that there are 
more stars optically contiguous, than would be likely if there 
were no special cause acting towards this end, and further that, 
if such a cause is in operation, it must be real, and not merely 
optical, contiguity that results from it. 

Let us analyse the argument more closely. By " mere chance 
as it might happen " Michell cannot be supposed to mean " un- 
caused/ 5 He is thinking of objective chance in the sense in 
which I have defined this in the preceding chapter. We 
speak of a chance occurrence when it is brought about by the 
coincidence of forces and circumstances so numerous and complex 
that knowledge sufficient for its prediction is of a kind altogether 
out of our reach. Michell uses the term vaguely but means, I 
think, something of this kind : An event is due to mere chance 
when it can only occur if a large number of independent 1 con- 
ditions are fulfilled simultaneously. The alternatives which 
Michell is discussing are therefore these : Are binary stars merely 
due to the interaction of a vast variety of stellar laws and posi- 
tions or are they the result of a few fundamental tendencies, 
which might be the subject of knowledge and which would lead 
us to expect such stars in relative profusion ? 

The existence of numerous binary stars may give a real 
inductive argument in favour of their arising out of the inter- 
action of a relatively small number of independent causes. But 
it is not possible to arrive at such precise results as MichelTs, 
If there is some finite probability d priori that binary stars, 
when they arise, do arise in this way, then, since the frequent 
coincidence of a given set of independent causes relatively few 
in number is more likely than that of a set relatively numerous, 
the observation of binary stars will raise this probability d pos- 
teriori to an extent which depends upon the relative profusion 
in which such stars appear. If, in short, the first of the two 
alternatives proposed above is assumed, there is no greater 
presumption for a distribution, covering a part of the heavens, 
in which binary stars appear, than for any other distribution ; 
if the second is assumed, there is a greater presumption. The 
observation of numerous distributions in which binary stars 
appear increases, therefore, by the inverse principle, any d priori 
probability which may exist in favour of the second hypothesis. 
1 See 3 of Note (ii.) to Part HE. 


But more than this the argument cannot justify. That MchelPs 
argument is, as it stands, no more valid than De Morgan's, 
becomes plain when we notice that he would still have a high 
probability for his conclusion even if only one binary star had 
been observed. The valuable part of the argument must clearly 
turn upon the observation of numerous binary stars. 

Let us now turn to MichelTs second step. He argues that, 
if binary stars arise out of the interaction of a small number of 
independent forces, they must be physically and not merely 
optically double. The force of this argument seems to depend 
upon our possessing previous knowledge as to the nature of the 
principal natural laws, and upon an assumption, arising out of 
this, that there are not likely to be forces tending to arrange 
stars, in reality at great distances from one another, so as to 
appear double from this particular planet. But Michell, in 
arguing thus, was neglecting the possibility that the optical 
connection between the stars might be due to the observer and 
his means of observation. It was not impossible that there should 
be a law, connected with the transmission of light for example, 
which would cause stars to appear to an observer to be much 
nearer together than they really are. 

While, therefore, a relative profusion of binary stars constitutes 
evidence favourably relevant to MichelTs conclusion, the argu- 
ment is more complex and much less conclusive than he seems to 
have supposed. This is a criticism which is applicable to many 
such arguments. The simplicity of the evidence, which arises 
out of the lack of much relevant information, is liable, unless we 
are careful, to lead us into deceptive calculations and into asser- 
tions of high numerical probabilities, upon which we should never 
venture in cases where the evidence is full and complicated, but 
where, in fact, the conclusion is established far more strongly. 
The enormously high probability in favour of his conclusion, to 
which Michell's calculations led him, should itself have caused 
him to suspect the accuracy of the reasoning by which he 
reached it. 

3. Some more recent problems of this type seem, however, so 
far as I am acquainted with them, to follow safer lines of argu- 
ment. The most important are concerned with the existence 
of star drifts. It seems to me not at all impossible to possess 
data on which a valid argument can be constructed from the 


observation of optically apparent star drifts to the probability 
of a real uniformity of motion amongst certain sets of stars 
relatively to others. 

Another problem, somewhat analogous to the preceding, has 
been recently discussed by Professor Karl Pearson. 1 The title 
might prove a little misleading, perhaps, until the explanation 
has been reached of the sense in which the term * random * is 
used in it. But Professor Pearson uses the term in a perfectly 
precise sense. He defines a random distribution as one in which 
spherical shells of equal volume about the sun as centre contain 
the same number of stars. 2 He" argues that the observed facts 
render probable the following disjunction : Either the distribu- 
tion of stars is not random in the sense defined above, or there is 
a correlation between their distance and their brilliancy, such as 
might be produced, for example, by the absorption of light in its 
transmission through space 5 or the space within which they all 
lie is limited in volume and not spherical in form. 3 But it is 
useless to employ the term random in this sense in such inquiries 
as MichelTs. For there is no reason to suppose that a non- 
random distribution is more likely than a random distribution 
to depend upon the interaction of a small number of independent 
forces, and there might even exist a presumption the other way. 
This arbitrary interpretation of randomness does not help us to 
the solution of any interesting problem. 

4 The discussion of final causes and of the argument from 
design has suffered confusion from its supposed connection with 
theology. But the logical problem is plain and can be determined 
upon formal and abstract considerations. The argument is in all 
cases simply this an event has occurred and has been observed 
which would be very improbable d priori if we did not know that 
it had actually happened ; on the other hand, the event is of such 
a character that it might have been not unreasonably predicted 
if we had assumed the existence of a conscious agent whose 
motives are of a certain kind and whose powers are sufficient. 

1 " On the Improhability of a Random Distribution of the Stars in Space," 
Proceedings of Royal Society, series A, vol. 84, pp. 47-70, 1910. 

2 It is, therefore, independent of direction, and the distribution is random 
even if the stars are massed in particular quarters of the heavens. The defini- 
tion is, therefore, exceedingly arbitrary. 

4 This should run more correctly, I think, " not a sphere mth the sun as 


Symbolically : Let h be our original data, a the occurrence 
of the event, b the existence of the supposed conscious agent. 
Then a/h is assumed very small in comparison with a/bh ; and 
we require 6/a&, the probability, that is to say, of 6 after a is 
known. The inverse principle of probability already demon- 
strated shows that blah = a/bh. ~^, and b/ah is therefore not 


determinate in terms of a/bh and a/h alone. Thus we cannot 
measure the probability of the conscious agent's existence after 
the event, unless we can measure its probability before the event. 
And it is our ignorance of this, as a rule, that we are endeavouring 
to remedy. The argument tells us that the existence of the 
hypothetical agent is more -likely after the event than before 
it ; but, as in the case of the general inductive problem dealt 
with in Part IIL, unless there is an appreciable probability first, 
there cannot be an appreciable probability afterwards. JSTo 
conclusion, therefore, which is worth iaving, can be based on the 
argument from design alone ; like induction, this type of argu- 
ment can only strengthen the probability of conclusions, for 
which there is something to be said on other grounds. We cannot 
say, for example, that the human eye is due to design more 
probably than not, unless we have some reason, apart from the 
nature of its construction, for suspecting conscious workmanship. 
But the necessary d priori probability, derived from some other 
source, may sometimes be forthcoming. The man who upon a 
desert island picks up a watch, or who sees the symbol John 
Smith traced upon the sand, can use with reason the argument 
from design. For he has other grounds for supposing that 
beings, capable of designing such objects, do exist, and that 
their presence on the island, now or formerly, is appreciably 

5. The most important problems at the present day, in which 
arguments of this kind are employed, are those which arise in 
connection with psychical research. 1 The analysis of the * cross- 

1 The probability that a remarkable success in naming playing cards is due 
to psychic agency, was discussed by Professor Edgeworth in MetretiJce. This 
was, I thini, the first application of probabilities to these questions. See also 
Proceedings of the Society for Psychical Research, Parts VTIL and X. ; Professor 
Edgeworth's article on Psychical Research and Statistical Method, Stat. Journ. 
vol. IxxsiL (1919) p. 222 ; and Experiments in Psychical Research at Leland 
Stanford Junior University, by J. Coover. 


correspondences/ which hare played so large a part in recent 
discussions, presents many points of difficulty which are not 
dissimilar to those which arise in other scientific inquiries of 
great complexity in which our initial knowledge is small. An 
important part of the logical problem, therefore, is to distinguish 
the peculiarity of psychical problems and to discover what special 
evidence they demand beyond what is required when we deal with 
other questions. There is a certain tendency, I think, arising out 
of the belief that psychical problems are in some way peculiar, 
to raise sceptical doubts against them, which are equally valid 
against all scientific proofs. Without entering into any questions 
of detail, let us endeavour to separate those difficulties which 
seem peculiar to psychical research from those ,which, however 
great, are not different from the difficulties which confront 
students of heredity, for instance, and which are not less likely 
than these to yield ultimately to the patience and the insight of 

For this purpose it is necessary to recur, briefly, to the analysis 
of Part III. It was argued there that the methods of empirical 
proof, by which we strengthen the probability of our conclusions, 
are not at all dissimilar, when we apply them to the discovery 
of formal truth, and when we apply them to the discovery of the 
laws which relate material objects, and that they may possibly 
prove useful even in the case of metaphysics ; but that the 
initial probability which we strengthen by these means is differ- 
ently obtained in each class of problem. In logic it arises out 
of the postulate that apparent self-evidence invests what seems 
self-evident with some degree of probability ; and in physical 
science, out of the postulate that there is a limitation to the 
amount of independent variety amongst the qualities of material 
objects. But both in logic and in physical science we may wish 
to consider hypotheses which it is not possible to invest with any 
d priori probability and which we entertain solely on account of 
the known truth of many of their consequences. An axiom 
which has no self -evidence, but which it seems necessary to com- 
bine with other axioms which are self-evident in order to deduce 
the generally accepted body of formal truth, stands in this 
category. A scientific entity, such as the ether or the electron, 
whose qualities have never been observed but whose existence we 
postulate for purposes of explanation, stands in it also. If the 


analysis of Part in. is correct, we can never attribute a finite 
probability * to the truth of such axioms or to the existence of 
such scientific entities, however many of their consequences 
we find to be true. They may be convenient hypotheses, because, 
if we confine ourselves to certain classes of their consequences, 
we are not likely to be led into error ; but they stand, neverthe- 
less, in a position altogether different from that of such generalis- 
ations as we have reason to invest with an initial probability. 

Let us now apply these distinctions to the problems of psychical 
research. In the case of some of them we can obtain the initial 
probability, I think, by the same kind of postulates as in physical 
science, and our conclusions need not be open to a greater degree 
of doubt than these. In the case of others we cannot ; and these 
must remain, unless some method is open to us peculiar to 
psychical research, as tentative unproved hypotheses in the 
same category as the ether. 

The best example of the first class is afforded by telepathy. 
We know that the consciousnesses which, if our hypothesis is 
correct, act upon one another, do exist ; and I see no logical differ- 
ence between the problem of establishing a law of telepathy and 
that of establishing the law of gravitation. There is at present a 
practical difference on account of the much narrower scope of our 
knowledge, in the case of telepathy, of cognate matters. We can, 
therefore, be much less certain ; but there seems no reason why 
we should necessarily remain less certain after more evidence 
has been accumulated. It is important to remember that, in 
the case of telepathy, we are merely discovering a relation be- 
tween objects which we already know to exist. 

The best example of the other class is afforded by attempts 
to attribute psychic phenomena to the agency of e spirits * other 
than human beings. Such arguments are weakened at present 
by the fact that no phenomena are known, so far as I am aware, 
which cannot be explained, though improbably in some cases, 
in other ways. But even if phenomena were to be observed of 

1 I am assuming that there is no argument, arising either from self-evidence 
or analogy, in addition to the argument arising from the truth of their con- 
sequences, in favour of the truth of such axioms or the existence of such objects ; 
but I daresay that this may not certainly be the case. The reader may be re- 
minded also that, when I deny a finite probability this is not the same thing as 
to affirm that the probability is infinitely smalL I mean simply that it is not 
greater than some numerically measurable probability. 


which no known agency could afford even an improbable ex- 
planation, the hypothesis of * spirits ' would still lie in the same 
logical limbo as the hypothesis of the ' ether,' in which they 
might be supposed not inappropriately to move. 

Such an hypothesis as the existence of ' spirits ' could only 
become substantial if some peculiar method of knowledge were 
within our power which would yield us the initial probability 
which is demanded. That such a method exists, it is not in- 
frequently claimed. If we can directly perceive these ' spirits/ 
as many of those who are described in James's Varieties of 
Religi&us Experience think they can, the problem is, logically, 
altogether changed. We have, in fact, very much the same kind 
of reason, though it may be with less probability, that we have 
for believing in the existence of other people. The preceding 
paragraph applies only to attempts at proving the existence of 
c spirits ' from such evidence as is discussed by the Society for 
Psychical Research. 

In between these two extremes comes a class of cases, with 
regard to which it is extremely difficult to come to a decision 
that of attempts to attribute psychic phenomena to the conscious 
agency of the dead. I wish to discuss here, not the nature of the 
existing evidence, but the question whether it is possible for 
any evidence to be convincing. In this case the object whose 
existence we are endeavouring to demonstrate resembles in 
many respects objects which we know to exist. The question 
of epistemology, which is before us, is this : Is it necessary, in 
order that we may have an initial probability, that the object of 
our hypothesis should resemble in every relevant particular 
some one object which we know to exist, or is it sufficient that we 
should know instances of all its supposed qualities, though never 
in combination ? It is clear that some qualities may be irrelevant 
position in time and space, for example and that * every 
relevant particular ' need not include these. But can the initial 
probability exist if our hypothesis assumes qualities, which have 
plainly some degree of relevance, in new combinations ? If we 
have no knowledge of consciousness existing apart from a living 
body, can indirect evidence of whatever character afford us any 
probability of such a thing ? Could any evidence, for example, 
persuade lis that a tree felt the emotion of amusement, even if 
it laughed repeatedly when we made jokes ? Yet the analogy 


which we demand seems to be a matter of degree ; for it does not 
seem unreasonable to attribute consciousness to dogs, although 
this constitutes a combination of qualities unlike in many respects 
to any which we know to exist. 

This discussion, however, is wandering from the subject of 
probability to that of epistemology, and it will not be solved until 
we possess a more comprehensive account of this latter subject 
than we have at present. I wish only to distinguish between those 
cases in which we obtain the initial probability in the same 
manner as in physical science from those in which we must get 
it, if at all, in some other way. The distinctions I have made 
are sufficiently summarised by a recapitulation of the following 
comparisons : We compared the proof of telepathy to the proof 
of gravitation, the proof of non-human * spirits * to the proof 
of the ether, and, much less closely, the proof of the consciousness 
of the dead to the proof of the consciousness of trees, or, perhaps, 
of dogs. 

Before passing to the next of the rather miscellaneous topics 
of this chapter, it may be worth while to add that we should be 
very chary of applying to problems of psychical research the 
caleuhis of probabilities. The alternatives seldom satisfy the 
conditions for the application of the Principle of Indifference, 
and the initial probabilities are not capable of being measured 
numerically. If, therefore, we endeavour to calculate the prob- 
ability that some phenomenon is due to ' abnormal ' causes, 
our mathematics -will be apt to lead us into unjustifiable 

6. Uninstructed common sense seems to be specially unre- 
liable in dealing with what are termed * remarkable occurrences.' 
Unless & * remarkable occurrence 9 is simply one which produces 
on us a particular psychological effect, that of surprise, we can 
only define it as an event which before its occurrence is very im- 
probable on the available evidence. But it will often occur 
whenever, in fact, our data leave open the possibility of a large 
number of alternatives and show no preference for any of them 
that every possibility is exceedingly improbable a priori. It 
follows, therefore, that what actually occurs does not iderive any 
peculiar significance merely from the fact of its being 'remarkable * 
in idie above sense. Something further is required before we 
can build with success. Yet MichelPs argument and the argu- 


ment from design derive a good deal of their plausibility, I think, 
from the e remarkable ' character of the actual constitution 
whether of the heavens or of the universe, in f orgetfulness of the 
fact that it is impossible to propound any constitution which 
would if it existed be other than ( remarkable/ It is supposed 
that a remarkable occurrence is specially in need of an explana- 
tion, and that any sufficient explanation has a high probability 
in its favour. That an explanation is particularly required, 
possesses a measure of truth ; for it is likely that our original 
data were much lacking in completeness, and the occurrence of 
the extraordinary event brings to light this deficiency. But 
that we are not justified in adopting with confidence any sufficient 
explanation, has been shown already. 

Such arguments, however, get a part of their plausibility from 
a quite different source. There is a general supposition that some 
kinds of occurrences are more likely than others to be susceptible 
of an explanation by us ; and, therefore, any explanation which 
deals with such cases falls in prepared soil. Results which, 
judging from ourselves, conscious agents would be likely to pro- 
duce fall into this category. Results which would be probable, 
supposing a direct and predominant causal dependence between 
the elements whose concomitance is remarked, belong to it also. 
There is, in fact, a sort of argument from analogy as to whether 
certain sorts of phenomena are or are not likely to be due to 
' chance.' This may explain, for example, why the particular 
concurrence of atoms that go to compose the human eye, why a 
series of correct guesses in naming playing cards, why special 
symmetry or special asymmetry amongst the stars, seem to 
require explanation in no ordinary degree. Prior to an explana- 
tion these particular concurrences or series or distributions are 
no more improbable than any other. But the causes of such 
conjunctions as these are more likely to be discoverable by the 
human mind than are the causes of others, and the attempt to 
explain them deserves, therefore, to be more carefully considered. 
This supposition, derived by analogy or induction from those 
cases in which we believe the causes to be known to us, has, per- 
haps, some weight. But the direct application of the Calculus 
of Probabilities can do no more in these cases than suggest matter 
for investigation. The fact that a man has made a long series 
of correct guesses in cases where he is cut off from the ordinary 


channels of communication, is a fact worthy of investigation, 
because it is more likely to be susceptible of a simple causal ex- 
planation, which may have many applications, than a case in 
which false and true guesses follow one another with no apparent 

7. In the case of empirical laws, such as Bode's law, which have 
no more than a very slight connection with the general body of 
scientific knowledge, it is sometimes thought that the law is more 
probable if it is proposed before the examination of some or all of 
the available instances than if it is proposed after their examina- 
tion. Supposing, for example, that Bode's law is accurately 
true for seven planets, it is held that the law would be more 
probable if it was suggested after the examination of six and 
was confirmed by the subsequent discovery of the seventh, than 
it would be if it had not been propounded until after all seven 
had been observed. The arguments in favour of such a conclusion 
are well put by Peirce : * " All the qualities of objects may be 
conceived to result from variations of a number of continuous 
variables ; hence any lot of objects possesses some character in 
common, not possessed by any other." Hence if the common 
character is not predesignate we can conclude nothing. Cases 
must not be used to prove a generalisation which has only been 
suggested by the cases themselves. He takes the first five poets 
from a biographical dictionary with their ages at death : 

Aagard . . .48 
Abeille ... 76 
Abulola . . .84 

Abunowas . , 48 
Accords . . 45 

" These five ages have the following characters in common : 

" 1, The difference of the two digits composing the number, 
divided by three, leaves a remainder of one. 

" 2. The first digit raised to the power indicated by the second, 
and then divided by three, leaves a remainder of one. 

" 3. The sum of the prime factors of each age, including one as 

a prime factor, is divisible by three' 3 
He compares a generalisation regarding the ages of poets based 

1 C. a Peirce, A Theory of Probable Inference, pp. 162-167 ; published in 
Jojms UopTdas Studies in Logic, 1883. 


on this evidence to Dr. Lyon Playfair's argument about the 
specific gravities of the three allotropic forms of carbon : 

Diamond . . . 3-48 
Graphite . . . 2-29=1/12 
Charcoal . . . 1-88 = 

approximately, the atomic weight of carbon being 12. Dr. 
Playf air thinks that the above renders it probable that the specific 
gravities of the allotropic forms of other elements would, if we 
knew them, be found to equal the different roots of their atomic 

The weakness of these arguments, however, has a different 
explanation. These inductions are very improbable, because they 
are out of relation to the rest of our knowledge and are based on 
a very small number of instances. The apparent absurdity, 
moreover, of the inductive law of Poets' Ages is increased by the 
fact that we take account of the knowledge we actually possess 
that the ages of poets are not in fact connected by any such law. 
If we knew nothing whatever about poets' ages except what is 
stated above, tlie induction would be as valid as any other which 
is based on a very weak analogy and a very small number of 
instances and is unsupported by indirect evidence. 

The peculiar virtue of prediction or predesignation is altogether 
imaginary. The number of instances examined and the analogy 
between them are the essential points, and the question as to 
whether a particular hypothesis happens to be propounded before 
or after their examination is quite irrelevant. If all our in- 
ductions had to be thought of before we examined the cases to 
which we apply them, we should, doubtless, make fewer induc- 
tions ; but there is no reason to think that the few we should make 
would be any better than the many from which we should be 
precluded. The plausibility of the argument is derived from a 
different source. If an hypothesis is proposed d priori, this 
commonly means that there is some ground for it, arising out of 
our previous knowledge, apart from the purely inductive ground, 
and if such is the case the hypothesis is clearly stronger than one 
which reposes on inductive grounds only. But if it is a mere 
guess, the lucky fact of its preceding some or all of the cases which 
verify it adds nothing whatever to its value. It is the union of 


prior knowledge, with, the inductive grounds which arise out of 
the immediate instances, that lends weight to an hypothesis, and 
not the occasion on which the hypothesis is first proposed. It is 
sometimes said, to give another example, that the daily fulfilment 
of the predictions of the Nautical Almanack constitutes the most 
cogent proof of the laws of dynamics. But here the essence of 
the verification lies in the variety of cases which can be brought 
accurately under our notice by means of the Almanack) and in 
the fact that they have all been obtained on a uniform principle, 
not in the fact that the verification is preceded by a prediction. 

The same point arises not uncommonly in statistical inquiries. 
If a theory is first proposed and is then confirmed by the examina- 
tion of statistics, we are inclined to attach more weight to it than 
to a tneory which is constructed in order to suit the statistics. 
But the fact that the theory which precedes the statistics is more 
likely than the other to be supported by general considerations 
for it has not, presumably, been adopted for no reason at all 
constitutes the only valid ground for this preference. If it does 
not receive more support than the other from general considera- 
tions, then the circumstances of its origin are no argument in its 
favour. The opposite view, which the unreliability of some 
statisticians has brought into existence, that it is a positive 
advantage to approach statistical evidence without preconcep- 
tions based on general grounds, because the temptation to ' cook ' 
the evidence will prove otherwise to be irresistible, has no 
logical basis and need only be considered when the i irtiality of 
an investigator is in doubt. 



1. GIVEN as our basis what knowledge we actually have, the 
probable, I have said, is that which it is rational for us to believe. 
This is not a definition. For it is not rational for us to believe 
that the probable is true ; it is only rational to have a probable 
belief in it or to believe it in preference to alternative beliefs. To 
believe one thing in 'preference to another, as distinct from believing 
the first true or more probable and the second false or less probable, 
must have reference to action and must be a loose way of ex- 
pressing the propriety of acting on one hypothesis rather than 
on another. We might put it, therefore, that the probable is 
the hypothesis on which it is rational for us to act. It is, however, 
not so simple as this, for the obvious reason that of two hypotheses 
it may be rational to act on the less probable if it leads to the 
greater good. We cannot say more at present than that the 
probability of a hypothesis is one of the things to be determined 
and taken account of before acting on it. 

2. I do not know of passages in the ancient philosophers which 
explicitly point out the dependence of the duty of pursuing 
goods on the reasonable or probable expectation of attaining 
them relative to the agent's knowledge. This means only that 
analysis had not disentangled the various elements in rational 
action, not that common sense neglected them. Herodotus 
puts the point quite plainly. " There is nothing more profitable 
for a man/' he says, " than to take good counsel with himself ; 
for even if the event turns out contrary to one's hope, still one's 
decision was right, even though fortune has made it of no effect : 
whereas if a man acts contrary to good counsel, although by luck 
he gets what he had no right to expect, his decision was not any 
the less foolish." * 

1 Herod, vii. 10. 


3. The first contact of theories of probability with mod 
ethics appears in the Jesuit doctrine of probabilism. Accord ; 
to this doctrine one is justified in doing an action for which there 
is any probability, however small, of its results being the best 
possible. Thus, if any priest is willing to permit an action, that 
fact affords some probability in its favour, and one will not be 
damned for performing it, however many other priests denounce 
it. 1 It may be suspected, however, that the object of this 
doctrine was not so much duty as safety. The priest who per- 
mitted you so to act assumed thereby the responsibility. The 
correct application of probability to conduct naturally escaped 
the authors of a juridical ethics, which was more interested in 
the fising of responsibility for definite acts, and in the various 
specified means by which responsibility might be disposed of, 
than in the greatest possible sum-total of resultant good. 

A more correct doctrine was brought to light by the efforts of 
the philosophers of the Port Royal to expose the fallacies of prob- 
abilism. " In order to judge," they say, " of what we ought to 
do in order to obtain a good and to avoid an evil, it is necessary 
to consider not only the good and evil in themselves, but also 
the probability of their happening and not happening, and to 
regard geometrically the proportion which all these things have, 
taken together." 2 Locke perceived the same point, although 
not so clearly, 3 By Leibniz this theory is advanced more 
explicitly ; in such judgments, he says, " as in other estimates 
disparate and heterogeneous and, so to speak, of more than one 
dimension, the greatness of that which is discussed is in reason 
composed of both estimates (i.e. of goodness and of probability), 
and is like a rectangle, in which there are two considerations, 
viz. that of length and that of breadth. . . . Thus we should 

1 Compare with, this doctrine the following curious passage from Jeremy 
Taylor: " We being the persons that are to be persuaded, we must see that 
we be persuaded reasonably. And it is nnreasonable to assent to a lesser 
evidence when a greater and clearer is propounded : but of that every man for 
himself is to take cognisance, if he be able to judge ; if he be not, he is not 
bound under the tie of necessity to know anything of it. That that is 
necessary shall be certainly conveyed to him : God, that best can, will certainly 
take care for that ; for if he does not, it becomes to be not necessary ; or if it 
should still remain necessary, and he be damned for not knowing it, and yet to 
know it be not in his power, then who can help it ! There can be no further 
care in this business." 

2 The Port Royal Logic (1662), Eng. Trans, p. 367. 

9 Essay concerning Human Understanding, book ii. chap. xxi. 66. 


' "1 need the art of thinking and that of estimating probabilities, 
; ..ades the knowledge of the value of goods and evils, in order 
properly to employ the art of consequences." 1 

In his preface to the Analogy Butler insists on " the absolute 
and formal obligation " under which even a low probability, 
if it is the greatest, may lay us : " To us probability is the very 
guide of life." 

4. With the development of a utilitarian ethics largely con- 
cerned with the summing up of consequences, the place of prob- 
ability in ethical theory has become much more explicit. But 
although the general outlines of the problem are now clear, there 
are some elements of confusion not yet dispersed. I will deal with 
some of them. 

In his Principia Ethica (p. 152) Dr. Moore argues that " the 
first difficulty in the way of establishing a probability that one 
course of action will give a better total result than another, lies 
in the fact that we have to take account of the effects of both 
throughout an infinite future. . . . We can certainly only pretend 
to calculate the effects of actions within what may be called an 
6 immediate future.' . . . We must, therefore, certainly have 
some reason to believe that no consequences of our action in a 
further future will generally be such as to reverse the balance of 
good that is probable in the future which we can foresee. This 
large postulate must be made, if we are ever to assert that the 
results of one action will be even probably better than those of 
another. Our utter ignorance of the far future gives us no justi- 
fication for saying that it is even probably right to choose the 
greater good within the region over which a probable forecast 
may extend." 

This argument seems to me to be invalid and to depend on 
a wrong philosophical interpretation of probability. Mr. Moore's 
reasoning endeavours to show that there is not even a 'probability 
by showing that there is not a certainty. We must not, of course, 
have reason to believe that remote consequences will generally 
be such as to reverse the balance of immediate good. But we 
need not be certain that the opposite is the case. If good is 
additive, if we have reason to think that of two actions one pro- 
duces more good than the other in the near future, and ii we have 
no means of discriminating between their results in the distant 
1 Nouveauz Essais, book ii, chap, xsl 


nire, then by what seems a legitimate application of the 
ineiple of Indifference we may suppose that there is a prob- 
ility in favour of the former action. Mr. Moore's argument 
ist be derived from the empirical or frequency theory of 
obability, according to which we muse know for certain what 
11 happen generally (whatever that may mean) before we can 
sert a probability. 

The results of our endeavours are very uncertain, but we have 

genuine probability, even when the evidence upon which it is 

unded is slight. The matter is truly stated by Bishop Butler : 

From our short views it is greatly uncertain whether this 

ideavour will, in particular instances, produce an overbalance 

: happiness upon the whole ; since so many and distant things 

lust come into the account. And that which makes it our duty 

that there is some appearance that it will, and no positive 

ppearance to balance this, on the contrary side. . . ." x 

The difficulties which exist are not chiefly due, I think, to our 

jnorance of the remote future. The possibility of our knowing 

hat one thing rather than another is our duty depends upon the 

ssumption that a greater goodness in any part makes, in the 

bsence of evidence to the contrary, a greater goodness in the 

rfiole more probable than would the lesser goodness of the part. 

i^e assume that the goodness of a part is favourably relevant to 

he goodness of the whole. Without this assumption we have no 

reason, not even a probable one, for preferring one action to any 

:>ther on the whole. If we suppose that goodness is always 

organic, whether the whole is composed of simultaneous or 

successive parts, such an assumption is not easily justified. The 

case is parallel to the question, whether physical law is organic or 

atomic, discussed in Chapter XXL 6. 

Nevertheless we can admit that goodness is partly organic 
and still allow ourselves to draw probable conclusions. For the 
alternatives, that either the goodness of the whole universe 
throughout time is organic or the goodness of the universe is the 
arithmetic sum of the goodnesses of infinitely numerous and 
infinitely divided parts, are not exhaustive. We may suppose 
that the goodness of conscious persons is organic for each distinct 

1 This passage is from the Analogy. The Bishop adds : " ... and also 
that such "benevolent endeavour is a cultivation of that most excellent of all 
virtuous principles, the active principle of benevolence." 


and individual personality. Or we may suppose that, when 
conscious units are in conscious relationship, then the whole 
which we must treat as organic includes both units. These are 
only examples. We must suppose, in general, that the units 
whose goodness we must regard as organic and indivisible are 
not always larger than those the goodness of which we can 
perceive and judge directly. 

5. The difficulties, however, which are most fundamental 
from the standpoint of the student of probability, are of a different 
kind. Normal ethical theory at the present day, if there can be 
said to be any such, makes two assumptions : first, that degrees 
of goodness are numerically measurable and arithmetically 
additive, and second, that degrees of probability also are numeric- 
ally measurable. This theory goes on to maintain that what 
we ought to add together, when, in order to decide between two 
courses of action, we sum up the results of each, are the c mathe- 
matical expectations ' of the several results. * Mathematical 
expectation ' is a technical expression originally derived from the 
scientific study of gambling and games of chance, and stands for 
the product of the possible gain with the probability of attaining 
it. 1 In order to obtain, therefore, a measure of what ought to 
be our preference in regard to various alternative courses of action, 
we must sum for each course of action a series of terms made 
up of the amounts of good which may attach to each of its 
possible consequences, each multiplied by its appropriate prob- 

The first assumption, that quantities of goodness are duly 
subject to the laws of arithmetic, appears to me to be open to a 
certain amount of doubt. But it would take me too far from 
my proper subject to discuss it here, and I shall allow, for the 
purposes of further argument, that in some sense and to some 
extent this assumption can be justified. The second assumption, 
however, that degrees of probability are wholly subject to the 
laws of arithmetic, runs directly counter to the view which has 

1 Priority in the conception of mathematical expectation can, I think, be 
claimed by Leibniz, De incerti aestimatione, 1678 (Coutnrat, Logique de Leibniz, 
p. 248). In a letter to Placcius, 1687 (Dutens, vt i. 36 and Coutnrat, op. cit. 
p. 246) Leibniz proposed an application of the same principle to juris- 
prudence, by virtue of which, if two litigants lay claim to a sum of money, 
and if the claim of the one is twice as probable as that of the other, the sum 
should be divided between them in that proportion. The doctrine, seems 
sensible, but I am not aware that it has ever been acted on. 


been advocated in Part I. of this treatise. Lastly, if both, these 
points be waived, the doctrine that the f mathematical expecta- 
tions * of alternative courses of action are the proper measures of 
our degrees of preference is open to doubt on two grounds first, 
because it ignores what I have termed in Part I. the * weights ' 
of the arguments, namely, the amount of evidence upon which 
each probability is founded ; and second, because it ignores the 
element of e risk ' and assumes that an even chance of heaven 
or hell is precisely as much to be desired as the certain attain- 
ment of a state of mediocrity. Putting on one side the first of 
these grounds of doubt, I will treat each of the others in turn. 

6. In Chapter III. of Part I. I have argued that only in a 
strictly limited class of cases are degrees of probability numeric- 
ally measurable. It follows from this that the c mathematical 
expectations ' of goods or advantages are not always numerically 
measurable ; and hence, that even if a meaning can be given to 
the sum of a series of non-numerical * mathematical expectations/ 
not every pair of such sums are numerically comparable in respect 
of more and less. Thus even if we know the degree of advantage 
which might be obtained from each of a series of alternative 
courses of actions and^know also the probability in each case of 
obtaining the advantage in question, it is not always possible by 
a mere process of arithmetic to determine which of the alternatives 
ought to be chosen. If, therefore, the question of right action is 
under all circumstances a determinate problem, it must be in 
virtue of an intuitive judgment directed to the situation as a 
whole, and not in virtue of an arithmetical deduction derived 
from a series of separate judgments directed to the individual 
alternatives each treated in isolation. 

We must accept the conclusion that, if one good is greater 
than another, but the probability of attaining the first less than 
that of attaining the second, the question of which it is our duty 
to pursue may be indeterminate, unless we suppose it to be 
within our power to make direct quantitative judgments of prob- 
ability and goodness jointly. It may be remarked, further, 
that the difficulty exists, whether the numerical indeterminate- 
ness of the probability is intrinsic or whether its numerical value 
is, as it is according to the Frequency Theory and most other 
theories, simply unknown. 

7. The second difficulty, to which attention is called above, 


is the neglect of tlie c weights ' of arguments in the conception 
of ' mathematical expectation.' In Chapter VI. of Part I. the 
significance of * weight' has been discussed. In the present 
connection the question comes to this if two probabilities are 
equal in degree, ought we, in choosing our course of action, to 
prefer that one which is based on a greater body of knowledge ? 

The question appears to me to be highly perplexing, and it is 
difficult to say much that is useful about it. But the degree of 
completeness of the information upon which a probability is 
based does seem to be relevant, as well as the actual magnitude 
of the probability, in making practical decisions. Bernoulli's 
maxim, 1 that in reckoning a probability we must take into account 
all the information which we have, even when reinforced by 
Locke's maxim that we must get all the information ^we can, 2 
does not seem completely to meet the case. If, for one alternative, 
the available information is necessarily small, that does not seem 
to be a consideration which ought to be left out of account 

8. The last difficulty concerns the question whether, the 
former difficulties being waived, the ' mathematical expectation ' 
of different courses of action accurately measures what our 
preferences ought to be whether, that is to say, the undesir- 
ability of a given course of action increases in direct proportion 
to any increase in the uncertainty of its attaining its object, or 
whether some allowance ought to be made for ' risk,' its undesir- 
ability increasing more than in proportion to its uncertainty. 

In fact the meaning of the judgment, that we ought to act in 
such a way as to produce most probably the greatest sum of 
goodness, is not perfectly plain. Does this mean that we 
ought so to act as to make the sum of the goodnesses of each of 
the possible consequences of our action multiplied by its prob- 
ability a maximum ? Those who rely on the conception of 
6 mathematical expectation ' must hold that this is an indisput- 
able proposition. The justifications for this view most commonly 
advanced resemble that given by Condorcet in his " K&Lexions 

1 Ars Conjectandi, p. 215 : " Non sufiicit expendere unum alterumve argu- 
mentum, sed conquirenda sunt omnia, quae in cognitionem nostram venire 
possunt, atque ullo modo ad probationem rei facere videntur." 

2 Essay concerning Human Understanding, book ii. chap. xxi. 67 : " He 
that judges without informing himself to the utmost that he is capable, cannot 
acquit himself of judging amiss." 


sur la r&gle generate, qtd prescrit de prendre pour valeur d'un 
evenement incertain, la probabilite de cet evenement multiplies 
par la valeur de 1' evenement en lui-meme," l where he argues 
from Bernoulli's theorem that such a rule will lead to satisfactory 
results if a very large number of trials be made. As, however, 
it will be shown in Chapter XXIX. of Part V. that Bernoulli's 
theorem is not applicable in by any means every case, this 
argument is inadequate as a general justification. 

In the history of the subject, nevertheless, the theory of 
f mathematical expectation ' has been very seldom disputed. 
As D'Alembert has been almost alone in casting serious doubts 
upon it (though he only brought himself into disrepute by doing 
so), it will be worth while to quote the main passage in which he 
declares his scepticism : " II me sembloit " (in reading Bernoulli's 
Ars Gonjectandi) " que cette matiere avoit besoin d'etre traitee 
d'une maniere plus claire ; je voyois bien que Tesperance 6toit 
plus grande, 1 que la somme esperee 6toit plus grande, 2 que 
la probabilite de gagner T6toit aussi. Mais je ne voyois pas avec 
la meme evidence, et je ne le vois pas encore, 1 que la probability 
soit estimee exactement par les m6thodes usitees ; 2 que quand 
elle le seroit, Tesperance doive Stre proportionnelle a cette proba- 
bilite simple, plutdt qu'a une puissance ou mSme a une fonction 
de cette probabilite ; 3 que quand il y a plusieurs combinaisons 
qui donnent differens avantages ou differens risques (qu'on 
regarde comme des avantages n6gatifs) il faille se contenter 
ftajoider simplement ensemble toutes les esperances pour avoir 
I'esp&ance totale." 2 

In extreme cases it seems difficult to deny some force to 
D'Alembert J s objection ; and it was with reference to extreme 
cases that he himself raised it. Is it certain that a larger good, 
which is extremely improbable, is precisely equivalent ethically 
to a smaller good which is proportionately more probable ? We 
may doubt whether the moral value of speculative and cautious 
action respectively can be weighed against one another in a 
simple arithmetical way, just as we have already doubted whether 
a good whose probability can only be determined on a slight 
basis of evidence can be compared by means merely of the 

1 Hist, de FAcad., Paris, 1781. 

* Opuscules mathematiques, vol. iv., 1768 (extraits de lettres), pp. 284, 285. 
See also p. 88 of the same volume. 


magnitude of this probability with, another good whose likelihood 
is based on completer knowledge. 

There seems, at any rate, a good deal to be said for the con- 
clusion that, other things being equal, that course of action is 
preferable which involves least risk, and about the results of 
which we have the most complete knowledge. In marginal cases, 
therefore, the coefficients of weight and risk as well as that 
of probability are relevant to our conclusion. It seems natural 
to suppose that they should exert some influence in other cases 
also, the only difficulty in this being the lack of any principle for 
the calculation of the degree of their influence. A high weight 
and the absence of risk increase pro tanto the desirability of the 
action to which they refer, but we cannot measure the amount 
of the increase. 

The risk * may be defined in some such way as follows. If 
A is the amount of good which may result, p its probability 
(p + q = l), and E the value of the ' mathematical expectation/ 
so that E=_pA, then the 'risk' is R, where R=^p(A-E) = 
y(l-^)A=ygA = yE. This may be put in another way: E 
measures the net immediate sacrifice which should be made in the 
hope of obtaining A ; q is the probability that this sacrifice will 
be made in vain ; so that #E is the ' risk/ 1 The ordinary theory 
supposes that the ethical value of an expectation is a function 
of E only and is entirely independent of E,. 

We could, if we liked, define a conventional coefficient c of 

weight and risk, such as c= - ~ - r, where w measures the 

* weight/ which is equal to unity when <p = l and w = l, and 
to zero when y=0 or w=0, and has an intermediate value 
in other cases. 2 But if doubts as to the sufficiency of the 
conception of e mathematical expectation ' be sustained, it is not 
likely that the solution will lie, as D'Alembert suggests, and as 
has been exemplified above, in the discovery of some more 

1 The tjheory of Bisiko is briefly dealt with by Czuber, WahrscheinUchkeits- 
rechnung, vol. ii. pp. 219 et seq, If R measures the first insurance, this leads to a 
Risiko of the second order, R^ = qR = # 2 E. This again may be insured against, 
and by a sufficient number of such reinsurances the risk can be completely 

shifted : E+B I +B 3 + . . .=E(l+q+q*+ . . .) = J?-=1LA. 

1 -q p 

2 If pA = p'A' t w>w r , and q=tf, then cA>c'A'; if pA=p'A' 9 w~w r , and 
g^<g / , then cA>c'A'; if pA=p'A', w>w r , and q<q' f then cA>c'A'; but if 
pA=3/A', w=.w' 9 and q>< 9 we cannot in general compare cA and c'A'. 


complicated function of tlie probability wherewith to compound 
the proposed good. The judgment of goodness and the judgment 
of probability both involve somewhere an element of direct 
apprehension, and both are quantitative. We have raised a 
doubt as to whether the magnitude of the * oughtness ' of an 
action can be in all cases directly determined by simply multi- 
plying together the magnitudes obtained in the two direct judg- 
ments ; and a new direct judgment may be required, respecting 
the magnitude of the c oughtness ' of an action under given 
circumstances, which need not bear any simple and necessary 
relation to the two former. 

The hope, which sustained many investigators in the course 
of the nineteenth century, of gradually bringing the moral sciences 
under the sway of mathematical reasoning, steadily recedes if 
we mean, as they meant, by mathematics the introduction of 
precise numerical methods. The old assumptions, that all 
quantity is numerical and that all quantitative characteristics 
are additive, can be no longer sustained. Mathematical reasoning 
now appears as an aid in its symbolic rather than in its numerical 
character. I, at any rate, have not the same lively hope as 
Condorcet, or even as Edgeworth, " eclairer les Sciences morales 
et politiques par le flambeau de TAlgfebre." In the present case, 
even if we are able to range goods in order of magnitude, and also 
their probabilities in order of magnitude, yet it does not follow 
that we can range the products composed of each good and its 
corresponding probability in this order. 

9, Discussions of the doctrine of Mathematical Expectation, 
apart from its directly ethical bearing, have chiefly centred 
round the classic Petersburg Paradox, 1 which has been treated by 
almost all the more notable writers, and has been explained by 
them in a great variety of ways. The Petersburg Paradox arises 
out of a game in which Peter engages to pay Paul one shilling 
if a head appears at the first toss of a coin, two shillings if it does 
not appear until the second, and, in general, 2 r ~ 1 shillings if no 
head appears until the r^ toss. What is the value of Paul's 
expectation, and what sum must he hand over to Peter before 
the game commences, if the conditions are to be fair 1 

1 3Tor the history of this paradox see Todhunter. The name is due, he says, 
to its having first appeared in a memoir by Daniel Bernoulli in the Commentarii 
of the Petersburg Academy. 



The mathematical answer is 2(|-) r 2 r " 1 , if the number of tosses 



is not in any case to exceed n in all, and 2(J) I< 2 1 ''" 1 if this restriction 



is removed. That is to say, Paul should pay - shillings in the 


first case, and an infinite sum in the second. Nothing, it is said, 
could be more paradoxical, and no sane Paul would engage on 
these terms even with an honest Peter. 

Many of the solutions which have been offered will occur at 
once to the reader. The conditions of the game imply contra- 
diction, say Poisson and Condorcet ; Peter has undertaken 
engagements which he cannot fulfil ; if the appearance of heads 
is deferred even to the 100th toss, he will owe a mass of silver 
greater in bulk than the sun. But this is no answer. Peter has 
promised much and a belief in his solvency will strain our imagina- 
tion ; but it is imaginable. And in any case, as Bertrand points 
out, we may suppose the stakes to be, not shillings, but grains of 
sand or molecules of hydrogen. 

D'Alembert's principal explanations are, first, that true ex- 
pectation is not necessarily the product of probability and 
profit (a view which has been discussed above), and second, that 
very long runs are not only very improbable, but do not occur 
at aU. 

The next type of solution is due, in the first instance, to Daniel 
Bernoulli, and turns on the fact that no one but a miser regards 
the desirability of different sums of money as directly proportional 
to their amount; as Buffon says, "L'avare est comme le 
math&tnaticien : tous deux estiment Fargent par sa quantity 
numerique." Daniel Bernoulli deduced a formula from the 
assumption that the importance of an increment is inversely 
proportional to the size of the fortune to which it is added. 
Thus, if a; is the c physical ' fortune and y the ' moral * fortune, 

, dx 

or yJclog-, where k and a are constants* 

On the basis of this formula of Bernoulli's a considerable 


theory has been built up both by Bernoulli 1 himself and by 
Laplace. 2 It leads easily to the further formula 

where a is the initial ' physical ' fortune, p l9 etc., the probabilities 
of obtaining increments x^ 9 etc., to a, and x the ' physical ' fortune 
whose present possession would yield the same * moral ' fortune 
as does the expectation of the various increments x^ etc. By 
means of this formula Bernoulli shows that a man whose fortune 
is 1000 may reasonably pay a 6 stake in order to play the 
Petersburg game with 1 units. Bernoulli also mentions two 
solutions proposed by Cramer. In the first all sums greater 
than 2- 4 (16,777,116) are regarded as e morally * equal ; this 
leads to 13 as the fair stake. According to the other formula 
the pleasure derivable from a sum of money varies as the square 
root of the sum ; this leads to 2 : 9s. as the fair stake. But 
little object is servecl by following out these arbitrary hypotheses. 

As a solution of the Petersburg problem this line of thought 
is only partially successful : if increases of * physical ' fortune 
beyond a certain finite limit can be regarded as ' morally ' 
negligible, Peter's claim for an infinite initial stake- from Paul is, 
it is true, no longer equitable, but with any reasonable law of 
diminution for successive increments Paul's stake will still remain 
paradoxically large. Daniel Bernoulli's suggestion is, however, 
of considerable historical interest as being the first explicit 
attempt to take account of the important conception known to 
modern economists as the diminishing marginal utility of money, 
& conception on which many important arguments are founded 
relating to taxation and the ideal distribution of wealth. 

Each of the above solutions probably contains a part of the 
psychological explanation. "We are unwilling to be Paul, partly 
because we do not believe Peter will pay us if we have good 
fortune in the tossing, partly because we do not know what we 
should do with so much money or sand or hydrogen if we won it, 
partly because we do not believe we ever should win it, and 
partly because we do not think it would be a rational act to risk 

1 "Specimen Theoriae Nov&e de Mensura Sortis," Comm. Acad. Petrop. 
vol. v. for 1730 and 1731, pp. 175-192 (published 1738). See Todhnnter, pp. 

213 - 

Theorie andlytigue, chap. x. " De Pesperanee morale," pp. 432-445. 


an infinite sum or even a very large finite sum for an infinitely 
larger one, whose attainment is infinitely unlikely. 

Wlien we have made the proper hypotheses and have elimin- 
ated these elements of psychological doubt, the theoretic dispersal 
of what element of paradox remains must be brought about, I 
think, by a development of the theory of risk. It is primarily 
the great risk of the wager which deters us. Even in the case 
where the number of tosses is in no case to exceed a finite number, 

the risk R, as already defined, may be very great, and the relative 

risk JST- will be almost unity. Where there is no limit to the 

number of tosses, the risk is infinite. A relative risk, which 
approaches unity, may, it has been already suggested, be a factor 
which must be taken into account in ethical calculation. 

10. In establishing the doctrine, that all private gambling 
must be with certainty a losing game, precisely contrary argu- 
ments are employed to those which do service in the Petersburg 
problem. The argument that " you must lose if only you go on 
long enough " is well known. It is succinctly put by Laurent : 1 
Two players A and B have a and b francs respectively. f(a) is 

the chance that A will be ruined. Thus f(a) = -* so that 

the poorer a gambler is, relatively to his opponent, the more 
likely he is to be ruined. But further, if b = <x> , f(a) = 1, i.e. ruin 
is certain. The infinitely rich gambler is the public. It is against 
the public that the professional gambler plays, and his ruin is 
therefore certain. 

Might not Poisson and Condorcet reply, The conditions of 
the game imply contradiction, for no gambler plays, as this argu- 
ment supposes, for ever ? 3 At the end of any finite quantity of 
play, the player, even if he is not the public, may finish, with 
winnings of any finite size. The gambler is in a worse position if 
his capital is smaller than his opponents' at poker, for instance, 
or on the Stock Exchange. This is clear. But our desire for 
moral improvement outstrips our logic if we tell HTT) that he 
must lose. Besides it is paradoxical to say that everybody 

1 Calcul des probability, p. 129. 

2 This would possibly follow from the theorem of Daniel Bernoulli. The 
reasoning by which Laurent obtains it seems to be the result of a mistake. 

8 Gf. also Mr. Bradley, Logic, p. 217. 


individually must lose and that everybody collectively must win. 
For every individual gambler who loses there is an individual 
gambler or syndicate of gamblers who win. The true moral is 
this, that poor men should not gamble and that millionaires 
should do nothing else. But millionaires gain nothing by gam- 
bling with one another, and until the poor man departs from the 
path of prudence the millionaire does not find his opportunity. 
If it be replied that in fact most millionaires are men originally 
poor who departed from the path of prudence, it must be 
admitted that the poor man is not doomed with certainty. 
Thus the philosopher must draw what comfort he can from the 
conclusion with which his theory furnishes him, that million- 
aires are often fortunate fools who have thriven on unfortunate 
ones. 1 

11. In conclusion we may discuss a little further the concep- 
tion of ' moral ' risk, raised in 8 and at the end of 9. Bernoulli's 
formula crystallises the undoubted truth that the value of a sum 
of money to a man varies according to the amount he already 
possesses. But does the value of an amount of goodness also 
vary in this way ? May it not be true that the addition of a given 
good to a man who already enjoys much good is less good than 
its bestowal on a man who has little ? If this is the case, it 
follows that a smaller but relatively certain good is better than 
a greater but proportionately more uncertain good. 

In order to assert this, we have only to accept a particular 
theory of organic goodness, applications of which are common 
enough in the mouths of political philosophers. It is at the root 
of all principles of equality, which do not arise out of an assumed 
rHmirnahrng marginal utility of money. It is behind the numerous 
arguments that an equal distribution of benefits is better than a 
very unequal distribution. If this is the case, it follows that, the 
sum of the goods of all parts of a community taken together 
being fixed, the organic good of the whole is greater the more 
equally the benefits are divided amongst the individuals. If the 
doctrine is to be accepted, moral risks, like financial risks, must 
not be undertaken unless they promise a profit actuarially. 

1 3Trom the social point of view, however, this moral against gambling may 
be drawn that those who start with the largest initial fortunes are most likely 
to win, and that a given increment to the wealth of these benefits them, on the 
assumption of a dfmfniflhmg marginal utility of money, less than it injures those 
from whom it is taken. 


There is a great deal which could be said concerning such a 
doctrine, but it would lead too far from what is relevant to the 
study of Probability. One or two instances of its use, however, 
may be taken from the literature of Probability. In his essay, 
" Sur 1'application du calcul des probability a 1'inoculation de 
la petite v6role," I D'Alembert points out that the community 
would gain on the average if, by sacrificing the lives of one in five 
of its citizens, it could ensure the health of the rest, but he argues 
that no legislator could have the right to order such a sacrifice. 
G-alton, in his Probability, the Foundation of Eugenics, employed 
an argument which depends essentially on the same point. 
Suppose that the members of a certain class cause an average 
detriment M to society, and that the mischiefs done by the 
several individuals differ more or less from M by amounts whose 
average is D, so that D is the average amount of the individual 
deviations, all regarded as positive, from M ; then, G-alton argued, 
the smaller D is, the stronger is the justification for taking such 
drastic measures against the propagation of the class as would 
be consonant to the feelings, if it were known that each individual 
member caused a detriment M. The use of such arguments 
seems to involve a qualification of the simple ethical doctrine 
that right action should make the sum of the benefits of the 
several individual consequences, each multiplied by its prob- 
ability, a maximum. 

On the other hand, the opposite view is taken in the Port Royal 
Logic and by Butler, when they argue that everything ought to 
be sacrificed for the hope of heaven, even if its attainment be 
thought infinitely improbable, since "the smallest degree of 
facility for the attainment of salvation is of higher value than 
all the blessings of the world put together." 2 The argument is, 
that we ought to follow a course of conduct which may with the 
slightest probability lead to an infinite good, until it is logically 
disproved that such a result of our action is impossible. The 
Emperor who embraced the Eoman Catholic religion, not because 

1 Opuscules mathematigues, vol. ii. 

2 Port Royal Logic (Eng. trans.), p. 369 : " It belongs to infinite things alone, 
as eternity and salvation, that they cannot be equalled by any temporal advan- 
tage ; and thus we ought never to place them in the balance with any of the 
things of the world. This is why the smallest degree of facility for the attain- 
ment of salvation is of higher value than all the blessings of the world put 
together. . . ." 



lie believed it, but because it offered insurance against a disaster 
whose future occurrence, however improbable, he could not 
certainly disprove, may not have considered, however, whether 
the product of an infinitesimal probability and an infinite good 
might not lead to a finite or infinitesimal result. In any case the 
argument does not enable us to choose between different courses 
of conduct, unless we have reason to suppose that one path is 
more likely than another to lead to infinite good. 

12. In estimating the risk, ' moral ' or ' physical/ it must be 
remembered that we cannot necessarily apply to individual 
cases results drawn from the observation of a long series re- 
sembling them in some particular. I am thinking of such argu- 
ments as Buffon's when he names ^~ as the limit, beyond 
which probability is negligible, on the ground that, being the 
chance that a man of fifty-six taken at random will die within a 
day, it is practically disregarded by a man of fifty-six who knows 
his health to be good. " If a public lottery/' Gibbon truly pointed 
out, " were drawn for the choice of an immediate victim, and if 
our name were inscribed on one of the ten thousand tickets, 
should we be perfectly easy 1 " 

Bernoulli's second axiom, 1 that in reckoning a probability 
we must take everything into account, is easily forgotten in these 
cases of statistical probabilities. The statistical result is so 
attractive in its definiteness that it leads us to forget the more 
vague though more important considerations which may be, in a 
given particular case, within our knowledge. To a stranger the 
probability that I shall send a letter to the post unstamped may 
be derived from the statistics of the Post Office ; for me those 
figures would have but the slightest bearing upon the question. 

13. It has been pointed out already that no knowledge of 
probabilities, less in degree than certainty, helps us to know what 
conclusions are true, and that there is no direct relation between 
the truth of a proposition and its probability. Probability begins 
and ends with probability. That a scientific investigation 
pursued on account of its probability mil generally lead to truth, 
rather than falsehood, is at the best only probable. The pro- 
position that a course of action guided by the most probable 
considerations will generally lead to success, is not certainly true 
and has nothing to recommend it but its probability. 

See p. 76. 


The importance of probability can only be derived from the 
judgment that it is rational to be guided by it in action ; and a 
practical dependence on it can only be justified by a judgment 
that in action we ought to act to take some account of it. It is 
for this reason that probability is to us the " guide of life," since 
to us, as Locke says, " in the greatest part of our concernment, 
God has afforded only the Twilight, as I may so say, of Prob- 
ability, suitable, I presume, to that state of Mediocrity and 
Probationership He has been pleased to place us in here." 






1. THE Theory of Statistics, as it is now understood, 1 can be 
divided into two parts which are for many purposes better kept 
distinct. The first function of the theory is purely descriptive. 
It devises numerical and diagrammatic methods by which certain 
salient characteristics of large groups of phenomena can be briefly 
described ; and it provides formulae by the aid of which we can 
measure or summarise the variations in some particular character 
which we have observed over a long series of events or instances. 
The second function of the theory is inductive. It seeks to extend 
its description of certain characteristics of observed events to 
the corresponding characteristics of other events which have not 
been observed. This part of the subject may be called the 
Theory of Statistical Inference ; and it is this which is closely 
bound up with the theory of probability. 

2. The union of these two distinct theories in a single science 
is natural. If, as is generally the case, the development of 
some inductive conclusion which shall go beyond the actually 
observed instances is our ultimate object, we naturally choose 
those modes of description, while we are engaged in our pre- 
liminary investigation, which are most capable of extension 
beyond the particular instances which they primarily describe. 
But this union is also the occasion of a great deal of confusion. The 
statistician, who is mainly interested in the technical methods of 
his science, is less concerned to discover the precise conditions in 
which a description can be legitimately extended by induction. 
He slips somewhat easily from one to the other, and having 
found a complete and satisfactory mode of description he 

1 See Yule, Introduction to Statistics, pp. 1-5, for a very interesting account 
of the evolution of the meaning of the term statistics. 



may take less pains over the transitional argument, which is 
to "permit him to use this description for the purposes of 

One or *two examples will show how easy it is to slip from 
description into generalisation. Suppose that we have a series 
of similar objects one of the characteristics of which is under 
observation ; a number of persons, for example; whose age at 
death has been recorded. We note the proportion who die at 
each age, and plot a diagram which displays these facts graphic- 
ally. We then determine by some method of curve fitting a 
mathematical frequency curve which passes with close approxima- 
tion through the points of our diagram. If we are given the 
equation to this curve, the number of persons who are comprised 
in the statistical series, and the degree of approximation (whether 
to the nearest year or month) with which the actual age has been 
recorded, we have a very complete and succinct account of one 
particular characteristic of what may constitute a very large 
mass of individual records. In providing this comprehensive 
description the statistician has fulfilled his first function. But in 
determining the accuracy with which this frequency curve can be 
employed to determine the probability of death at a given age 
in the population at large, he must pay attention to a new class 
of considerations and must display a different kind of capacity. 
He must take account of whatever extraneous knowledge may be 
available regarding the sample of the population which came 
under observation, and of the mode and conditions of the observa- 
tions themselves. Much of this may be of a vague kind, and most 
of it will be necessarily incapable of exact, numerical, or statistical 
treatment. He is faced, in fact, with the normal problems of 
inductive science, one of the data, which must be taken into 
account, being given in a convenient and manageable form by 
the methods of descriptive statistics. 

Or suppose, again, that we are given, over a series of years, 
the marriage rate and the output of the harvest in a certain area 
of popidation. We wish to determine whether there is any 
apparent degree of correspondence between the variations of the 
two within this field of observation. It is technically difficult to 
measure such degree of correspondence as may appear to exist 
between the variations in two series, the terms of which are in 
some manner associated in couples, by coincidence, in this case, 


of time and place. By the method of correlation tables and 
correlation coefficients the descriptive statistician is able to effect 
this object, and to present the inductive scientist with a highly 
significant part of his data in a compact and instructive form. 
But the statistician has not, in calculating these coefficients of 
observed correlation, covered the whole ground of which the in- 
ductive scientist must take cognisance. He has recorded the 
results of the observations in circumstances where they cannot 
be recorded so clearly without the aid of technical methods ; but 
the precise nature of the conditions in which the observations 
took place and the numerous other considerations of one sort or 
another, of which we must take account when we wish to 
generalise, are not usually susceptible of numerical or statistical 

The truth of this is obvious ; yet, not unnaturally, the more 
complicated and technical the preliminary statistical investigations 
become, the more prone inquirers are to mistake the statistical 
description for an inductive generalisation. 1 This tendency, 
which has existed in some degree, as, I think, the whole history of 
the subject shows, from the eighteenth century down to the 
present time, has been further encouraged by the terminology in 
ordinary use. For several statistical coefficients are given the 
same name when they are used for purely descriptive purposes, 
as when corresponding coefficients are used to measure the force 
or the precision of an induction. The term 'probable error/ 
for example, is used both for the purpose of supplement- 
ing and improving- a statistical description, and for the 
purpose of indicating the precision of some generalisation. 
The term * correlation ' itself is used both to describe an 
observed characteristic of particular phenomena and, in the 
enunciation of an inductive law which relates to phenomena 
in general. 

3. I have been at pains to enforce this contrast between 
statistical description and statistical induction, because the 
chapters which follow are to be entirely about the latter, whereas 
nearly all statistical treatises aje mainly concerned with the 
former. My object will be to analyse, so far as I can, the logical 

1 Of. Whitehead, Introduction to Mathematics, p. 27 : " There is no more 
common error than to assume that, because prolonged and accurate mathe- 
matical calculations have been made, the application of the result to some fact 
of nature is absolutely certain." 


basis of statistical modes of argument. This involves a double 
task. To mark down those which, are invalid amongst argu- 
ments having the support of authority is relatively easy. 
The other branch of our investigation, namely, to analyse 
the ground of validity in the case of those arguments the 
force of which all of us do in fact admit, presents the same 
kind of fundamental difficulties as we met with in the case 
of Induction. 

4. The arguments with which we have to deal fall into three 
main classes : 

(i.) Given the probability relative to certain evidence of each 
of a series of events, what are the probabilities, relative to the 
same evidence, of various proportionate frequencies of occurrence 
for the events over the whole series ? Or more briefly, how often 
may we expect an event to happen over a series of occasions, given 
its probability on each occasion ? 

(ii.) Given the frequency with which an event has occurred 
on a series of occasions, with what probability may we expect it 
on a farther occasion ? 

(iii.) Given the frequency with which an event has occurred 
on a series of occasions, with what frequency may we probably 
expect it on a further series of occasions ? 

In the first type of argument we seek to infer an unknown 
statistical frequency from an d priori probability. In the second 
type we are engaged on the inverse operation, and seek to base 
the calculation of a probability on an observed statistical fre- 
quency. In the third type we seek to pass from an observed 
statistical frequency, not merely to the probability of an individual 
occurrence, but to the probable values of other unknown statistical 

Each of these types of argument can be further complicated 
by being applied not simply to the occurrence of a simple event 
but to the concurrence under given conditions of two or more 
events. When this two or more dimensional classification re- 
places the one dimensional, the theory becomes what is some- 
times termed Correlation, -as distinguished from simple Statis- 
tical [Frequency. >-r 

5. In Chapter XXVIII. I touch briefly on the observed 
phenomena which have given rise to the so-called Law of 
Great Numbers, and the discovery of which first set statistical 


investigation going. In Chapter XXIX. the first type of argu- 
ment, as classified above, is analysed, and the conditions which 
are recpdred for its validity are stated. The crucial problem 
of attacking the second and third types of argument is the 
subject of my concluding chapters. 



Natura quidem suas habet consuetudines, natas ex reditu causarum, sed non 
nisi ws M TO TroXtf. Novi morbi inundant subinde hunianum genus, quodsi 
ergo de mortibus quotcunque experiments feceris, non ideo naturae rerum limifces 
posuisti, ut pro future variare non possit. LEIBNIZ in a letter to Bernoulli, 
December 3, 1703. 

1. IT has always been known that, while some sets of events 
invariably happen together, other sets generally happen together. 
That experience shows one thing, while not always a sign of 
another, to be a usual or probable sign of it, must have been one 
of the earliest and most primitive forms of knowledge. If a dog 
is generally given scraps at table, that is sufficient for him to judge 
it reasonable to be there. But this kind of knowledge was slow 
to be made precise. Numerous experiments must be carefully 
recorded before we can know at all accurately how usual the 
association is. It would take a dog a long time to find out that 
he was given scraps except on fast days, and that there was the 
same number of these in every year. 

The necessary kind' of knowledge began to be accumulated 
during the seventeenth and eighteenth centuries by the early 
statisticians. Halley and others began to construct mortality 
tables ; the proportion of the births of each sex were tabulated ; 
and so forth. These investigations brought to light a new fact 
which had not been suspected previously namely, that in certain 
cases of partial association the degree of association, i.e. the pro- 
portion of Distances in which it existed, shows a very surprising 
regularity, and that this regularity becomes more marked the 
greater the number of the instances under consideration. It was 
found, for example, not merely that boys and girls are born on 
the whole in about equal proportions, but that the proportion, 



wHcli is not one of complete equality, tends everywhere, when 
the number of recorded instances becomes large, to approximate 
towards a certain definite figure. 

During the eighteenth century matters were not pushed much 
further than this, that in certain cases, of which comparatively 
few were known, there was this surprising regularity, increasing 
in degree as the instances became more numerous. Bernoulli, 
however, took the first step towards giving it a theoretical basis 
by showing that, if the d priori probability is known throughout, 
then (subject to certain conditions which he himself did not make 
clear) in the long run a certain determinate frequency of occurrence 
is to be expected. Siissmileh (Die gottliche Ordnung in den 
Terdnderungen des menschlichen Geschlechts, 1741) discovered a 
theological interest in these regularities. Such ideas had become 
sufficiently familiar for Gibbon to characterise the results of 
probability as " so true in general, so fallacious in particular." 
Kant found in them (as many later writers have done) some 
bearing on the problem of Free Will. 1 

But with the nineteenth century came bolder theoretical 
methods and a wider knowledge of facts* After proving his 
extension of Bernoulli's Theorem, 2 Poisson applied it to the 
observed facts, and gave to the principle underlying these 
regularities the title of the Law of Great Numbers. " Les choses 
de toutes natures/' he wrote, 3 " sont soumises a une loi univer- 
selle qu'on peut appeler la loi des grands nombres. . . . De ces 
exernples de toutes natures, il r&ulte que la loi universelle des 
grands nombres est deja pour nous un fait general et incontestable, 
r&ultant d'exp&riences qui ne se d&nentent jamais." This is 
the language of exaggeration ; it is also extremely vague. Bitt 

1 In Idee zu einer aUgemeinen Geschichte in weUburgerlicher Absicht, 1784. For 
a discussion of this passage and for the connection between Kant and Siissmileh, 
see Lottin's Quetdet, pp. 367, 368. 

3 See p. 345. 

8 Recherches, pp. 7-12. Von Bortkiewicz (Kritische Betrachtungen, 1st part, 
pp. 655-660) has maintained that Poisson intended to state his principle in a 
less general way than that in which it has been generally taken, and that he was 
misunderstood by Quetelet and others. If we attend only to Poisson's con- 
tributions to Comptes Eendus in 1S35 and 1836 and to the examples he gives 
there, it is possible to make out a good case for thinking that he intended his 
law to extend only to cases where certain strict conditions were fulfilled. But 
this is not the spirit of his more popular writings or of the passage quoted above. 
At any rate, it is the fashion, in which Poisson influenced his contemporaries, 
that is historically interesting ; and this is certainly not represented by Von 
Bortkiewicz's interpretation. 


it is exciting ; it seems to open up a whole new field to scientific 
investigation ; and it has had a great influence on subsequent 
thought. Poisson seems to claim that, in the whole field of chance 
and variable occurrence, there really exists, amidst the apparent 
disorder, a discoverable system. Constant causes are always 
at work and assert themselves in the long run, so that each class 
of event does eventually occmc in a definite proportion of cases. 
It is not clear how far Poisson's result is due to d priori reasoning, 
and how far it is a natural law based on experience ; but it is 
represented as displaying a certain harmony between natural 
law and the d priori reasoning of probabilities. 

Poisson's conception was mainly popularised through the 
writings of Quetelet. In 1823 Quetelet visited Paris on an 
astronomical errand, where he was introduced to Laplace and 
came into touch with " la grande ecole frangaise." " Ma jeunesse 
et mon zele," he wrote in later years, " ne tarderent pas a me 
mettre en rapport avec les homines les plus distinguSs de cette 
e*poque ; qu'on me permette de citer Fourier, Poisson, Lacroix, 
specialement connus, conrmne Laplace, par leurs excellents Merits 
sur la the*orie math&natique des probabilites. . . . C'est done 
au milieu des savants, statisticiens, et 6conomistes de ce temps 
que j'ai commence" mes travaux." 1 Shortly afterwards began 
his long series of papers, extending down to 1873, on the applica- 
tion of Probability to social statistics. He wrote a text-book 
on Probability in the form of letters for the instruction of the 
Prince Consort. 

Before accepting in 1815 at the age of nineteen (with a view to 
a livelihood) a professorship of mathematics, Quetelet had studied 
as an art student and written poetry ; a year later an opera, of 
which he was part-author, was produced at Ghent. The character 
of his scientific work is in keeping with these beginnings. There 
is scarcely any permanent, accurate contribution to knowledge 
which can be associated with his name. But suggestions, pro- 
jects, far-reaching ideas he could both conceive and express, and 
he has a very fair claim, I think, to be regarded as the parent of 
modern statistical method. 

Quetelet very much increased the number of instances of the 

1 For the details of the life of Quetelet and for a very full discussion- of his 
writings with special reference to Probability, see Lottin's Quetelet, statteticien et 


Law of Great Numbers, and also brought into prominence a 
slightly variant type of it, of which a characteristic example is 
the law of height, according to which the heights of any consider- 
able sample taken from any population tend to group themselves 
according to a certain well-known curve. His instances were 
chiefly drawn from social statistics, and many of them were of a 
kind well calculated to strike the imagination the regularity of 
the number of suicides, " Peffrayante exactitude avec laquelle 
les crimes se reproduisent," and so forth. Quetelet writes 
with an almost religious awe of these mysterious laws, and 
certainly makes the mistake of treating them as being as 
adequate and complete in themselves as the laws of physics, 
and as little needing any further analysis or explanation. 1 
Quetelet's sensational language may have given a considerable 
impetus to the collection of social statistics, but it also involved 
statistics in a slight element of suspicion in the minds of some 
who, like Comte, regarded the application of the mathematical 
calculus of probability to social science as " purement chim6rique 
et, par consequent, tout a fait vicieuse." The suspicion of 
quackery has not yet disappeared. Quetelet belongs, it must be 
admitted, to the long line of brilliant writers, not yet extinct, who 
have prevented Probability from becoming, in the scientific salon, 
perfectly respectable. There is still about it for scientists a 
smack of astrology, of alchemy. 

The progress of the conception since the time of Quetelet has 
been steady and uneventful ; and long strides towards this perfect 
respectability have been taken. Instances have been multiplied 
and the conditions necessary for the existence of statistical 
stability have been to some extent analysed. While the most 
fruitful applications of these methods have still been perhaps, 
as at first, in social statistics and in errors of observation, a 
number of itses for them have been discovered in quite recent 
times in the other sciences; and the principles of Mendelism 
have opened out for them a great field of application throughout 

1 Compare, for instance, the following passage from Recherches sur le penchant 
au crime : " H me semble que ce qui se rattaohe a Tesp&ce humaine, considered 
en masse, est de I'ordre des faits physiques ; plus le nombre des individus est 
grand, plus la volonte individuelle s'efface et laisse predominer la serie des f aits 
generaux qui dependent des causes ge'ne'rales. . . . Ce sont ces causes qu'il 
s'agit de saisir, et des qu'on les connaStra, on en de'terminera les effets pour la 
Boci6t comme on determine 3es effets par les causes dans les sciences physiques." 


2. The existence of numerous instances of the Law of Great 
Numbers, or of something of the kind, is absolutely essential for 
the importance of Statistical Induction. Apart from this the more 
precise parts of statistics, the collection of facts for the prediction 
of future frequencies and associations, would be nearly useless. 
But the ' Law of Great Numbers * is not at all a good name for the 
principle which underlies Statistical Induction. The e Stability 
of Statistical Frequencies ' would be a much better name for it. 
The former suggests, as perhaps Poisson intended to suggest, but 
what is certainly false, that every class of event shows statistical 
regularity of occurrence if only one takes a sufficient number of 
instances of it. It also encourages the method of procedure, by 
which it is thought legitimate to take any observed degree of 
frequency or association, which is shown in a fairly numerous 
set of statistics^ and to assume with insufficient investigation 
that, because the statistics are numerous, the observed degree of 
frequency is therefore stable. Observation shows that some 
statistical frequencies are, within narrower or wider limits, stable. 
But stable frequencies are not very common, and cannot be 
assumed lightly. 

The gradual discovery, that there are certain classes of 
phenomena, in which, though it is impossible to predict what will 
happen in each individual case, there is nevertheless a regularity 
of occurrence if the phenomena be considered together in succes- 
sive sets, gives the clue to the abstract inquiry upon which we 
are about to embark. 



Hoc igitur est Ulud Problema, quod evulgandum hoc loco proposui, post- 
quam jam per vicennium pressi, efc cujus turn novitas, turn summa utilitas cum 
pan conjuncta dif&cultate omnibus reliquis hujus doctrinae capitibus pondus 
et pretium superaddere potest. 

1. BERNOULLI 5 s Theorem is generally regarded as the central 
theorem of statistical probability. It embodies the first attempt 
to deduce the measures of statistical frequencies from the measures 
of individual probabilities, and it is a sufficient fruit of the twenty 
years which Bernoulli alleges that he spent in reaching his result, 
if out of it the conception first arose of general laws amongst 
masses of phenomena, in spite of the uncertainty of each parti- 
cular case. But, as we shall see, the theorem is only valid subject 
to stricter qualifications, than have always been remembered, 
and in conditions which are the exception, not the rule, 

The problem, to be discussed in this chapter, is as follows : 
Given a series of occasions, the probability 2 of the occurrence 
of a certain event at each of which is known relative to certain 
initial data h, on what proportion of these occasions may we 
reasonably anticipate the occurrence of the event ? Given, that 
is to say, the individual probability of each of a series of events 
a priori, what statistical frequency of occurrence of these events 
is to be anticipated over the whole series ? Beginning with 
Bernoulli's Theorem, we will consider the various solutions of 
this problem which have been propounded, and endeavour to 

1 Ars Conjectandi, p. 227. 

2 In the simplest cases, dealt with by Bernoulli, these probabilities are all 
supposed equal 

337 Z 


etenoine the proper limits within which each method has 


2. Bernoulli's Theorem in its simplest form is as follows : If 

he probability of an event's occurrence under certain conditions 

s p, then, if these conditions are present on m occasions, the most 
probable number of the event's occurrences is mp (or the nearest 
integer to this), i.e. the most probable proportion of its occurrences 
bo the total number of occasions is p ; further, the probability 
that the proportion of the event's occurrences will diverge from 
the most probable proportion p by less than a given amount 6, 
increases as m increases, the value of this probability being 
calculable by a process of approximation. 

The probability of the event's occurring n times and failing 
m - n times out of the m occasions is (subject to certain conditions 
to be elucidated later) p n q m ' n multiplied by the coefficient of 
this expression in the expansion of (p + q) m 9 where p + q = I. If 

wi \ 

we write n=mp-h, this term is =r-j- irrPV*" 11 - I* 

* (mp-h) ! (mq+h) r * 

is easily shown that this is a maximum when h = 0, i.e. when n = mp 
(or the nearest integer to this, where mp is not integral). This 
result constitutes the first part of Bernoulli's Theorem. 

For the second part of the theorem some method of approxi- 
mation is required. Provided that m is large, we can simplify 

fn> \ 

the expression ; rr-r-^ Tr t p n Q m ~ n by means of Stirling's 

r (mp-h) I (mq+h) I J & 

Theorem, and obtain as its approximate value 

As before, this is a ma.-giTnTi-m when & = 0, i.e. when n = mp. 

It is possible, of course, by more complicated formulae to 
obtain closer approximations than this. 1 But there is an objec- 
tion, which can be raised to this approximation, quite distinct 
from the fact that it does not furnish a result correct to as many 
places of decimals as it might. This is, that the approximation 
is independent of the sign of h, whereas the original expression 
is not thus independent. That is to say, the approximation 
implies a symmetrical distribution for different values of h about 

1 See, e.g.> Bowley, Memerds of Statistics, p. 298. The objection about to 
be raised does not apply to these closer approximations. 


the value for A=0 ; while the expression under approximation 
is unsymmetrical. It is easily seen that this want of symmetry 
is appreciable unless mpq is large. We ought, therefore, to have 
laid it down as a condition of our approximation, not only that 
m must be large, but also that mpq must be large. Unlike most 
of my criticisms, this is a mathematical, rather than a logical 
point. I recur to it in 15. 

" Par une fiction qui rendra les calculs plus faciles " (to quote 
Bertrand), we now replace the integer h by a continuous variable 
z and argue that the probability that the amount of the diverg- 
ence from the most probable value mp will lie between z and z + dz } 

This * fiction 9 will do no harm so long as it is remembered that we 
are now dealing with a particular kind of approximation. The 
probability that the divergence h from the most probable value 
mp will be less than some given quantity a is, therefore, 



If we put ;* =t, this is equal to 


Thus, if we write a = j^/Smpq 7, the probability l that the 
number of occurrences will lie between 

mp -f *t/2mpq 7 and mp - +/2mpq 7 

2 f y 
is measured by 2 =1 e~* dt. This same expression measures 

>v ^J o 

1 The replacement of the integer h by the continuous variable z may render 
the formula rather deceptive. It is certain, for example, that the error does not 
lie between h and A + 1. 

a The above proof follows the general lines of Bertrand's (Calcul des proba- 
bilites, chap. iv.). Some writers, using rather mere precision, give the result as 

(e.g. Laplace, by the use of Euler's Theorem, and more recently Czuber, 


the probability that the proportion of occurrences will He 

2 f 
The different values of the integral -7=- 1 6 "'"* = () are given 


in tables. 1 

The probability that the proportion of occurrencesjwill lie 

between given limits varies with the magnitude of / 9 and 

this expression is sometimes used, therefore, to measure the 
* precision ' of the series. Given the d priori probabilities, the 
precision varies inversely with the sguare root of the number of 
instances. Thus, while the probability that the absolute diverg- 
ence will be less than a given amount a decreases, the probability 
that the corresponding proportionate divergence (i.e. the absolute 
divergence divided by the number of instances) will be less than 
a given amount 6, increases, as the number of instances increases. 
This completes the second part of Bernoulli's Theorem. 

3. Bernoulli himself was not acquainted with Stirling's 
theorem, and his proof differs a good deal from the proof outlined 
in 2. His final enunciation of the theorem is as follows : If in 
each of a given series of experiments there are r contingencies 
favourable to a given event out of a total number of contingencies 

t, so that - is the probability of the event at each experiment, 


then, given any degree of probability c, it is possible to make such 
a number of experiments that the probability, that the propor- 
tionate number of the event's occurrences will lie between 

and , is greater than c. 2 
t t 

WahrsoTieinlicJikeitereclinung, vol. i. p. 121). As the whole formula is approxi- 
mate, the simpler expression given in the text is probably not loss satisfactory in 
practice. See also Czuber, Erdwicklung, pp. 76, 77, and Eggenberger, Reitrage 
zur Darstellung des JSsrnoullwcTien Theorems. 

1 A list of the principal tables is given by Czuber, loc. cit. vol. i. p. 122. 

2 Ara Conjectandi, p. 236 (I have translated freely). There is a brief account 
of Bernoulli's proof in Todhunter's History, pp. 71, 72. The problem is dealt 
with by Laplace, TMorie analytique, livre ii. chap, iii. For an account of 
Laplace's proof see Todhunter*s History, pp. 548-553. 


4. We seem, therefore, to have proved that, if the d priori 
probability of an event under certain conditions is p, the pro- 
portion of times most probable d priori for the event's occurrence 
on a series of occasions where the conditions are satisfied is also 
p, and that if the series is a long one the proportion is very un- 
likely to differ widely from p. This amounts to the principle 
which Ellis x and Venn have employed as the defining axiom of 
probability, save that if the series is ' long enough ' the proportion, 
according to them, will certainly be p. Laplace 2 believed that the 
theorem afforded a demonstration of a general law of nature, and 
in his second edition published in 1814 he replaces 3 the eloquent 
dedication, A Napoleon-le-Grand, which prefaces the edition of 
1812, by an explanation. that Bernoulli's Theorem must always 
bring about the eventual downfall of a great power which, drunk 
with the love of conquest, aspires to a universal domination, 
" c'est encore un r&ultat du calcul des probabilites, confirme 
par de nombreuses et funestes experiences." 

5. Such is the famous Theorem of Bernoulli which some have 
believed 4 to have a universal validity and to be applicable to all 
6 properly calculated ' probabilities. Yet the theorem exhibits 
algebraical rather than logical insight. And, for reasons about 
to be given, it will have to be conceded that it is only true of a 
special class of cases and requires conditions, before it can be 
legitimately applied, of which the fulfilment is rather the ex- 
ception than the rule. For consider the case of a coin of which 
it is given that the two faces are either both heads or both tails : 
at every toss, provided that the results of the other tosses are 
unknown, the probability of heads is J and the probability of 
tails is J ; yet the probability of m heads and m tails in 2m tosses 

1 On the Foundation of the Theory of Probabilities : " If the probability of a 
given event bo correctly determined, the event will on a long run of trials tend 
to recur with frequency proportional to this probability. This is generally 
proved mathematically. It seems to mo to be true d priori. ... I have been 
unable to sever the judgment that one event is more likely to happen than 
another from the belief that in the long run it will occur more frequently." 

2 Essai philosophigue, p. 53 : "On peut tirer du theoreme pr6c<dent cette 
consequence qui doit tre regardee comme une loi g&ierale, savoir, que les 
rapports des effets de la nature, sont a fort peu pres constans, quand ces effets 
sont considered en grand nombre." 

3 Introduction, pp. liii, liv. 

* Even by Mr. Bradley, Principles of Logic, p. 214. After criticising Venn's 
view he adds : " It is false that the chances must be realised in a series. It is, 
however, true that they most probably will be, and true again that this prob- 
ability is increased, the greater the length we give to our series." 


is zero, and it is certain d priori that there will be either 2w 
heads or none. Clearly Bernoulli's Theorem is inapplicable to 
such a case. And this is but an extreme case of a normal 

For the first stage in the proof of the theorem assumes that, 
if p is the probability of one occurrence, p r is the probability of r 
occurrences running. Our discussion of the theorems of multi- 
plication will have shown how considerable an assumption this 
involves. It assumes that a knowledge of the fact that the event 
has occurred on every one of the first r - 1 occasions does not in 
any degree affect the probability of its occurrence on the rth. 
Thus Bernoulli's Theorem is only valid if our initial data are of 
such a character that additional knowledge, as to the proportion 
of failures and successes in one part of a series of cases is alto- 
gether irrelevant to our expectation as to the proportion in another 
part. If, for example, the initial probability of the occurrence 
of an event under certain circumstances is one in a million, we 
may only apply Bernoulli's Theorem to evaluate our expectation 
over a million trials, if our original data are of such a character 
that, even after the occurrence of the event in every one of the 
first million trials, the probability in the light of this additional 
knowledge that the event will occur on the next occasion is still 
no more than one in a million. 

Such a condition is very seldom fulfilled. If our initial prob- 
ability is partly founded upon experience, it is clear that it is 
liable to modification in the light of further experience. It is, 
in fact, difficult to give a concrete instance of a case in which the 
conditions for the application of Bernoulli's Theorem are com- 
pletely fulfilled. At the best we are dealing in practice with a 
good approximation, and can assert that no realised series of 
moderate length can much affect our initial probability. If we 

2 f y 
wish to employ the expression ~ I e'^dt we are in a worse 

position. For this is an approximate formula which requires for 
its validity that the series should be long ; whilst it is precisely 
in this event, as we have seen above, that the use of Bernoulli's 
Theorem is more than usually likely to be illegitimate. 

6. The conditions, which have been described above, can be 
expressed precisely as follows : 


Let m x n represent the statement that the event has occurred 
on m out of n occasions and has not occurred on the others ; and 
let !#i/A p> where Ti represents our d priori data, so that p is the 
a priori probability of the event in question. Bernoulli's Theorem 
then requires a series of conditions, of which the following is 
typical : m +iX tl +i/ m x n . ^= 1 x 1 /A, i.e. the probability of the event 
on the n + 1th occasion must be unaffected by our knowledge of 
its proportionate frequency on the first n occasions, and must be 
exactly equal to its d priori probability before the first occasion. 

Let us select one of these conditions for closer consideration. 
If y r represents the statement that the event has occurred on each 
of r successive occasions, y r l^^y r lyr--J l -2//--i/^ an d so on, so 


that y r jTi^ TiyJy^Ji. Hence if we are to have y r fh= s p r , we 


must have yjy^^=p for all values of s from 1 to r. But in 
many particular examples y 8 /y,,,-Ji increases with s, so that 
y r /A># r . Bernoulli's Theorem, that is to say, tends, if it is 
carelessly applied, to exaggerate the rate at which the probability 
of a given divergence from the most probable decreases as the 
divergence increases. If we are given a penny of which we have 
no reason to doubt the regularity, the probability of heads at 
the first toss is | ; but if heads fall at every one of the first 999 
tosses, it becomes reasonable to estimate the probability of heads 
at the thousandth toss at much more than J. For the d priori 
probability of its being a conjurer's penny, or otherwise biassed 
so as to fall heads almost invariably; is not usually so infinitesim- 
ally small as (|) 1000 . We can only apply Bernoulli's Theorem 
with rigour for a prediction as to the penny's behaviour over a 
series of a thousand tosses, if we have d priori such exhaustive 
knowledge of the penny's constitution and of the other con- 
ditions of the problem that 999 heads running would not cause 
us to modify in any respect our prediction d priori. 

7. It seldom happens, therefore, that we can apply Bernoulli's 
Theorem with reference to a long series of natural events. For 
in such cases we seldom possess the exhaustive knowledge which 
is necessary. Even where the series is short, the perfectly 
rigorous application of the Theorem is not likely to be legiti- 
mate, and some degree of approximation will be involved in 
utilising its results. 

Not so infrequently, however, artificial series can be devised 


in which the assumptions of Bernoulli's Theorem are relatively 
legitimate. 1 Given, that is to say, a proposition a l} some series 
o 1 a 2 . . . can be found, which satisfies the conditions : 


Adherents of the Frequency Theory of Probability, who use the 
principal conclusion of Bernoulli's Theorem as the defining pro- 
perty of all probabilities, sometimes seem to mean no more than 
that, relative to given evidence, every proposition belongs to 
some series, to the members of which Bernoulli's Theorem is 
rigorously applicable. But the natural series, the series, for 
example, in which we are most often interested, where the a's 
are alike in being accompanied by certain specified conditions c, 
is not, as a rule, rigorously subject to the Theorem. Thus * the 
probability of a in certain conditions c is J ' is not in general 
equivalent, as has sometimes been supposed, to e It is 500 to 1 
that in 90,000 occurrences of c, a will not occur more than 20,200 
times, and 500 to 1 that it will not occur less than 19,800 times.' 

8. Bernoulli's Theorem supplies the simplest formula by 
which we can attempt to pass from the d priori probabilities of 
each of a series of events to a prediction of the statistical frequency 
of their occurrence over the whole series. We have seen that 
Bernoulli's Theorem involves two assumptions, one (in the form 
in which it is usually enunciated) tacit and the other explicit. 
It is assumed, first, that a knowledge of what has occurred at 
some of the trials would not affect the probability of what may 
occur at any of the others ; and it is assumed, secondly, that these 
probabilities are all equal d priori. It is assumed, that is to say, 
that the probability of the event's occurrence at the rth trial is 
equal d priori to its probability at the nth trial, and, further, that 
it is unaffected by a knowledge of what may actually have 
occurred at the nth trial. 

A formula, which dispenses with the explicit assumption of 
equal d priori probabilities at every trial, was proposed by 
Poisson, 2 and is usually known by his name. It does not dispense, 

1 In the discussion in Chapter 31VJ., p. 170, of the probability of a diverg- 
ence from an equality of heads and tails in coin-tossing, an example has been 
given of the construction of an artificial series in which the application of 
Bernoulli's Theorem is more legitimate than in the natural series. 

2 Recherches, pp. 246 et seq. 


however, with the other inexplicit assumption. The difference 
between Poisson's Theorem and Bernoulli's is best shown by 
reference to the ideal case of balls drawn from an urn. The 
typical example for the valid application of Bernoulli's Theorem 
is that of balls drawn from a single urn, containing black and 
white balls in a known proportion, and replaced after each draw- 
ing, or of balls drawn from a series of urns, each containing black 
and white balls in the same known proportion. The typical 
example for Poisson's Theorem is that of balls drawn from a series 
of urns, each containing black and white balls in different known 

Poisson's Theorem may be enunciated as follows : a Let s 
trials be made, and at the Xth trial (X = 1, 2 ... s) let the prob- 
abilities for the occurrence and non-occurrence of the event be 


Pte g\ respectively. Then, if ^-^=_p, the probability that the 


number of occurrences m of the event in the s trials will lie 
between the limits spl is given by 


x I 

By substituting - -== and - - = y, this maybe written 

in a form corresponding to that of Bernoulli's Theorem, 2 namely : 
The probability that the number of occurrences of the event 
will lie between spyk^/s is given by 

9. This is a highly ingenious theorem and extends the applica- 
tion of Bernoulli's results to some important types of cases.- It 
embraces, for example, the case in which the successive terms of 
a series are drawn from distinct populations known to be char- 
acterised by differing statistical frequencies ; no further com- 

1 For the proof see Poisson, Recherches, loc. cit., or Czuber, Wahrscheirilich- 
keitsrechnung, voL i. pp. 153-159. 

2 For the analogous form of Bernoulli's Theorem see p. 339 (footnote). 


plication being necessary beyond the calculation of two simple 
functions of these frequencies and of the number of terms in the 
series. But it is important not to exaggerate the degree to which 
Poisson's method has extended the application of Bernoulli's 
results. Poisson's Theorem leaves untouched all those cases in 
which the probabilities of some of the terms in the series of events 
can be influenced by a knowledge of how some of the other terms 
in the series have turned out. 

Amongst these cases two types can be distinguished. In the 
first type such knowledge would lead us to discriminate between 
the conditions to which the different instances are subject. If, 
for example, balls are drawn from a bag, containing black and 
white balls in known proportions, and not replaced, the know- 
ledge whether or not the first ball drawn was black affects the 
probability of the second ball's being black because it tells us 
how the conditions in which the second ball is drawn differ 
from those in which the first ball was drawn. In the second type 
such knowledge does not lead us to discriminate between the 
conditions to which the different instances are subject, but it leads 
us to modify our opinion as to the nature of the conditions which 
apply to all the terms alike. If, for instance, balls are drawn 
from a bag, which is one, but it is not certainly known which, out 
of a number of bags containing black and white balls in differing 
proportions, the knowledge of the colour of the first ball drawn 
affects the probabilities at the second drawing, because it throws 
some light upon the question as to which bag is being drawn from. 

This last type is that to which most instances conform which 
are drawn from the real world. A knowledge of the character- 
istics of some members of a population may give us a clue to the 
general character of the population in question. Yet it is this 
type, where there is a change in knowledge but no change in the 
material conditions from one instance to the next, which is most 
frequently overlooked. 1 It will be worth while to say something 
further about each of these two types. 2 

1 Numerous instances could be quoted. To take a recent English ex- 
ample, reference may be made to Yule, Introduction to the Theory of Statistics, 
p. 251. Mr. Yule thinks that the condition of independence is satisfied if " the 
result of any one throw or toss does not affect, and is unaffected by, the results 
of the preceding and following tosses," and does not allow for the cases in which 
knowledge of the result is relevant apart from any change in the physical con- 

a The types which I distinguish under four heads (the BernouQian, the 


10. For problems of the first type, where there is physical 
or material dependence between the successive trials, it is not 
possible, I think, to propose any general solution ; since the 
probabilities of the successive trials may be modified in all kinds 
of different ways. But for particular problems, if the conditions 
are precise enough, solutions can be devised. The problem, for 
instance, of an urn, containing black and white balls in known 
proportions, from which balls are drawn successively and not 
replaced) 3 - is ingeniously solved by Czuber 2 with the aid of 
Stirling's Theorem. If a is the number of balls and s the number 
of drawings, he reaches the interesting conclusion (assuming that 
cr, s and cr - $ are all large) that the probability of the number of 
black balls lying within given limits is the same as it would be 
if the balls were replaced after each drawing and the number 

of drawings were - s instead of s. 

In addition to the assumptions already stated, Professor 
Czuber's solution applies only to those cases where the limits, for 
which we wish to determine the probability, are narrow compared 
with the total number of black balls p<r. Professor Pearson 3 has 
worked out the same problem in a much more general manner, 
so as to deal with the whole range, i.e. the frequency or prob- 
ability of all possible ratios of black balls, even where $>pcr. The 
various forms of curve, which result, according to the different 
relations existing between p, s, and <r, supply examples of each 
of the different types of frequency curve which arise out of a 

Poissonian, and tlie two described above) Bachelier (Calcul ties probability, 
p. 155) classifies as follows : 

(i.) When the conditions are identical throughout, the problem has uni- 

(ii.) When they vary from stage to stage, but according to a law given from 
the beginning and in a manner which does not depend upon what has happened 
at the earlier stages, it has independance 

(iii.) When they vary in a manner which depends upon what has happened 
at the earlier stages, it has conne&ite. 

Bachelier gives solutions for each type on the assumption that the number of 
trials is very great, and that the number of successes or failures can be regarded 
as a continuous variable. This is the same kind of assumption as that made 
in the proof of Bernoulli's Theorem given in 2, and is open to the same objec- 
tions, or rather the value of the results is limited in the same way. 

1 It is of no consequence whether the balls are drawn successively and not 
replaced, or are drawn simultaneously* 

2 Loc. cit. vol. i. pp. 163, 164. 

3 " Skew Variation in Homogeneous Material," Phil. Trans. (1895), p. 360. 


classification according to (i.) skewness or symmetry, (ii.) limita- 
tion of range in one, both or neither direction ; and he designates, 
therefore, the curves which are thus obtained as generalised prob- 
ability curves. His discussion of the properties of these curves is 
interesting, however, to the student of descriptive statistics 
rather than to the student of probability. The most generalised 
and, mathematically, by far the most elegant treatment of this 
problem, with which I am acquainted, is due to Professor 
Tschuprow. 1 

Poisson, in attempting a somewhat similar problem, 2 arrives 
at a result, which seems obviously contrary to good sense, by a 
curious, but characteristic, misapprehension of the meaning of 
e independence ' in probability. His problem is as follows : 
If I balls be taken out from an urn, containing c black and white 
balls in known proportions, and not replaced, and if a further 
number of balls /x. be then taken out, the probability that a given 


proportion - of these //. balls will be black is independent of 
r r 

the number and the colour of the I balk originally drawn out. For, 
he argues, if l + p balls are drawn out, the probability of a com- 
bination, which is made up of I black and white balls in given 
proportions followed by p balls, of which m are white and n black, 
must be the same as that of a similar combination in which the 
p, balls precede the I balls. Hence the probability of m white 
balls in /j, drawings, given that the Z balls have already been 
drawn out, must be equal to the probability of the same result, 
when no balls have been previously drawn out. The reader will 
perceive that Poisson, thinking only of physical dependence, has 
been led to his paradoxical conclusion by a failure to distinguish 
between the cases where the proportion of black and white balls 
amongst the I balls originally drawn is known and where it is not. 
The fact of their having been drawn in certain proportions, pro- 
vided that only the total number drawn is known and the pro- 
portions are unknown, does not influence the probability. Poisson 
states in his conclusion that the probability is independent of the 
number and colour of the I balls originally drawn. If he had 
added as he ought * provided the number of each colour is 

1 "Zur Theorie der Stabilitat statistischer Eeihon," p. 216, published in 
the Skandinavisk Aktuarietidskrift for 1919. 
* Loc. cit. pp. 231, 232. 


unknown* the air of paradox disappears. This is an exceedingly 
good example of the failure to perceive that a probability cannot 
be influenced by the occurrence of a material event but only by 
such knowledge) as we may have, respecting the occurrence of the 
event. 1 

11. For problems of the second type, where knowledge of the 
result of one trial is capable of influencing the probability at the 
next apart from any change in the material conditions, there is, 
likewise, no general solution. The following artificial example, 
however, will illustrate the sort of considerations which are in- 

In the cases where Bernoulli's Theorem is applied to practical 
questions, the d priori probability is generally obtained empiric- 
ally by reference to the statistical frequency of each alternative 
in past experience under apparently similar conditions. Thus 
the d priori probability of a male birth is estimated by reference 
to the recorded proportion of male births in the past. 2 The 
validity of estimating probabilities in this manner will be dis- 
cussed later. But for the purposes of this example let us assume 
that the d priori probability has been calculated on this basis. 

Thus the d priori probability p ( = - ) of an event is based on 

the observation of its occurrence r times out of s occasions on 
which the given conditions were present. Now, according to 
Bernoulli's Theorem directly applied, the probability of the 

event's occurring n times running is p n or ( - ) . But, if the 

\ S J 
event occurs at the first trial, the probability at the second 

1 Por an attempt to solve other problems of this type see Bachelior, Calcul 
des probability, chap. is. (Probability connexes). I think, however, that the 
solutions of this chapter are vitiated by his assuming in tho course of them 
both that certain quantities are very large, and also, at a later stage, that the 
same quantities are infinitesimal. On this account, for example, his solution 
of the following difficult problem breaks down : Given an urn A with m white 
and n black balls and an urn B with m' white and n' black balls, if at each move 
a ball is taken from A and put into B, and at the same time a ball is taken from 
B and put into A, what is the probability after x moves that the urns A and B 
shall have a given composition ? 

2 Of. Yule, Theory of Statistics, p. 258 : " We are not able to assign an 
d priori value to the chance p (i.e. of a male birth) as in the case of dice-throwing, 
but it is quite sufficiently accurate for practical purposes to use the proportion 
of male births actually observed if that proportion be based on a moderately 
large number of observations.'* 


becomes , and so on. Hence the probability P, properly 

calculated, of n successive occurrences is 

T r + 1 r + 2 r+n-1^ 
s'sTT s+2 s-Mi-1 


(r + -!)! (5-1)1 
-l)! (r-l)l 

j\s+?i - > e - OS-HI - iy- - 6 - (r - 1) 
Theorem, provided that r and s are large ; 



where Q 

Thus, in this case, the assumption of Bernoulli's Theorem is 
approximately correct, only if Q is nearly unity. This condition 
is not satisfied unless n is small both compared with r and com- 
pared with 5. It is very important to notice that two conditions 
are involved. Not only must the experience, upon which the 
d priori probability is based, be extensive in comparison with the 
number of instances to which we apply our prediction ; but also 
the number of previous instances multiplied by the probability 
based upon them, i.e. $p (=r), must be large in comparison with 
the number of new instances. Thus, even where the prior ex- 
perience, upon which we found the initial probability P, is very 
extensive, we must not, if P is very small, say that the probability 
of n successive occurrences is approximately p % 9 unless n is also 
small. Similarly if we wish to determine, by the methods of 
Bernoulli, the probability of n occurrences and m failures on 
m 4- n occasions, it is necessary that we should have m and n small 


compared with s 9 n small compared with r, and m small compared 
.with s-r. 1 

The case solved above is the simplest possible. The general 
problem is as follows : If an event has occurred x times in the 

7* ~h3? 

first y trials, its probability at the y + 1th is ; determine the 

a priori probability of the event's occurring p times in q trials, 
If the d priori probability in question is represented by <f>(p, q), we 

have 0(p, q) = * <t>(p -!,?-!) + * . *-<f>(p, q - 1). 

S T q 1 O -T ({ 

I know of no solution of this, even approximate. But we may 
say that the conditions are those of supernormal dispersion as 
compared with Bernoulli's conditions. That is to say, the prob- 

ability of a proportion differing widely from - is greater than 


in Bernoullian conditions ; for when the proportion begins to 
diverge it becomes more probable that it will continue to diverge 
in the same direction. If, on the other hand, the conditions of 
the problem had been such, that when the proportion begins to 
diverge it becomes more probable that it will recover itself and 

tend back towards - (as when we draw balls without replacing 


them from a bag of known composition), we should have sub- 
normal dispersion. 2 

12. The condition elucidated in the preceding paragraph is 
frequently overlooked by statisticians. The following example 
from Czuber 8 will be sufficient for the purpose of illustration. 
Czuber's argument is as follows : 

In the period 1866-1877 there were registered in Austria 

m- 4,311,076 male births 
n= 4,052,193 female births 

5 = 8,363,269; 

1 This paragraph is concerned with a different point from that dealt with 
in Professor Pearson's article " On the Influence of Past Experience on Future 
Expectation," to which it bears a superficial resemblance. Professor Pearson's 
article which deals, not with Bernoulli's Theorem, but with Laplace's " Rule of 
Succession,* 9 will be referred to in 16 of this chapter and in 12 of the next. 

a Bachelier (Calcul ties probability, p. 201) classifies these two kinds of con- 
ditions as conditions acc&eratrices and conditions retardatrices. 

8 Loc. cit. vol. ii. p. 15. I choose my example from Professor Czuber because 
he is usually so careful an exponent of theoretical statistics. 


for the succeeding period, 1877-1899, we are given only 
m r = 6,533,961 male births ; 

what conclusion can we draw as to the number n' of female 
births ? We can conclude, according to Czuber, that the most 
probable value 

. nm f KQ _ 

% = = 6,141,587, 

u m 

and that there is a probability P = -9999779 that n f will lie 
between the limits 6,118,361 and 6,164,813. 

It seems in plain opposition to good sense that on 
such evidence we should be able with practical certainty 

p = . 9999779 = 1 -1 to estimate the number of female 

45250 / 

births within such narrow limits. And we see that the con- 
ditions laid down in 11 have been flagrantly neglected. The 
number of eases, over which the prediction based on Bernoulli's 
Theorem is to extend, actually exceeds the number of cases upon 
which the d priori probability has been based. It may be added 
that for the period, 1877-1894, the actual value of n f did lie 
between the estimated limits, but that for the period, 1895- 
1905, it lay outside limits to which the same method had 
attributed practical certainty. 

That Professor Czuber should have thought his own argument 
plausible, is to "be explained, I think, by his tacitly taking account 
in his own mind of evidence not stated in the problem. He was 
relying upon the fact that there is a great mass of evidence for 
believing that the ratio of male to female births is peculiarly 
stable. But he has not brought this into the argument, and he 
has not used as his d priori probability and as his coefficient of 
dispersion the values which the whole mass of this evidence would 
have led him to adopt. Would not the argument have seemed 
very preposterous if m had been the number of males called 
Greorge, and n the number of females called Mary ? Would it not 
have seemed rather preposterous if m had been the number of 
legitimate births and n the number of illegitimate births ? Clearly 
we must take account of other considerations than the mere 
numerical values of m and n in estimating our d priori probability. 
But this question belongs to the subject-matter of later chapters, 


and, quite apart from the manner of calculation of the d priori 
probability, the argument is invalidated by the fact than an 
d priori probability founded on 8,363,269 instances, without 
corroborative evidence of a non-statistical character, cannot 
be assumed stable through a calculation which extends over 
12,700,000 instances. 

13. Before we leave the theorems of Bernoulli and Poisson, 
it is necessary to call attention to a very remarkable theorem by 
Tchebycheff, from which both of the above theorems can be 
derived as special cases. This result is reached rigorously and 
without approximation, by means of simple algebra and without 
the aid of the differential calculus. Apart from the beauty 
and simplicity of the proof, the theorem is so valuable and so 
little known that it will be worth while to quote it in full : * 

Let x, y, z . . . represent certain magnitudes, of which x 
can take the values x^x 2 . . . as k with probabilities p-$% . . . p^ 
respectively, y the values y^/ z . . . y l with probabilities q^ . . .q l9 
z the values z^z z . . . z m with probabilities r^ . . . r m and so on, 
so that 

k I TO 

2p = l, Sjl, 2r = l, etc. 

Js I wi 

Write 2p K x K = a, %y A = &, Srs =c, etc., 


fc I in 

and SpA a -i, %yA 2 = & l5 $Vy 2 = c > etc -> 

i i i 

so that we can describe a as the mathematical expectation or 
average value of x, and % as the mathematical expectation or 
average value of a 2 , etc. 

The probability that the sum x + y + z+ . . . will have for 
its value ^ K ^-y\+^+ - is A?^ . . . (provided that the 
values of x, y, z . . . are independent). Hence 

i Prom Journ. Liouville (2), xii., 1867, " Des valeurs moyennes," an article 
translated from the Russian of Tchebycheff. This proof is also quoted by 
Czuber, loc. cit. p. 212, through whom I first became acquainted with it. Most 
of TchebychefPs work was published previous to 1870 and appeared originally 
in Russian. It was not easily accessible, therefore, until the publication at 
Petrograd in 1907 of the collected edition of his works in French. His 
theorems are, consequently, not nearly so well known as they deserve to be, 
although his most important theorems were reproduced from time to time in 
the journals of Euler and Liouville. For full references eee the Bibliography. 



S^+yx + ^H- ... -a-6-c- . - 0^?A'V 
summed for all values of K, X, /^ is the average expectation for 

Now S 

Also 2& r fi . . . = 1, summed for all values of X, /*..., and 

7j *- 

22(0, - a)(y A - &)A 

-ab-ay^ + db) = 0. 
Therefore 2(a? je +y A + + ' - - --6-^- 


where the summation extends over all values of K, X, p . . . and 
a is some arbitrary number greater than unity. 

If we omit those terms of the sum on the left-hand side of 
the above equation for which 

and write unity for this expression in the remaining terms, both 
these processes diminish the magnitude of the left-hand side. 

Hence Sp^ft^. ..<-, where the summation covers those sets 
of values only for which 

If P is the probability that 

is equal to or less than unity, it follows that 


- 2 

~ 2 - 


Hence the probability that the sum 

X K +2/\ + + - lies between the limits 


is greater than 1 ^, where a is some number greater than 



This result constitutes Tchebycheff's Theorem. It may also 
be written in the following form : 

Let n be the number of the magnitudes x, y, z . . ., and 

write a= **; then the probability that the arithmetic 


X K -f 2/x + +..-,. -, . ,, T -, 

mean -- ^ - lies between the limits 


a + 5 + G + . . . 1 A*! + &(_ 4- fin -K . . tt 2 -f ft 3 -I- 6' 2 -f- . . . 

is greater than 1 


It is also easy to show 1 as a deduction from Tchebycheff's 
Theorem that, if an amount A is won when an event of probability 
p[p = 1 - q\ occurs and an amount B lost when it fails, then in 
s trials the probability that the total winnings (or losses) will lie 
between the limits 

is greater than 1 - ^ 


14. From this very general result for the probable limits of 
a sum composed of a number of independently varying magni- 
tudes, Bernoulli's Theorem is easily derived. For let there be 

1 For a proof soe Czubcr, IOG. ciL vol. i. p. 210. 



IT. v 

s observations or trials, and s magnitudes x^x^ . . . x g corre- 
sponding, such that # = 1 when the event under consideration 
occurs, and $=0 when it fails. If the probability of the event's 
occurrence is p y we have a~p, b=p, etc., and a^p, \*=p, etc. 
Hence the probability P that the number of the event's occur- 
rences will lie between the limits spa^sp-$p 2 } i.e. between 

the limits spa^/spq where g = l-j>, is >l-~. If we 

compare this formula with the formula for Bernoulli's 
Theorem already given, we find that, where this formula 

gives P>1 g, Bernoulli's Theorem with greater precision 

gives P = ( rA The degree of superiority in the matter 

\ v 2 / 

of precision supplied by the latter can be illustrated by the 
following table : 



Vt 7 ' 




















Thus when the limits are narrow and a is small, Bernoulli's 
formula gives a value of P very much in excess of 1 . But 

Bernoulli's formula involves a process of approximation which is 
only valid when s is large. Tchebycheff's formula involves no 
such process and is equally valid for all values of s. We have 
seen in 11 that there are numerous cases in which for a 
different reason Bernoulli's formula exaggerates the results, 
and, therefore, Tchebycheff's more cautious limits may some- 
times prove useful. 

The deduction of a corresponding form of Poisson's Theorem 
from Tchebycheff's general formula obviously follows on similar 
lines. For we put 1 a -ft, &=p 25 etc., and fl^-ft, b^p 29 etc., 
1 I am using the same notation as that used for Poisson's Theorem in 8. 


and find that the probability that the number of the event's 
occurrences will lie between the limits 


a V Spx- 

i.e. between the limits sp a v 2; 
i.e. between the limits sp *J%ak *Js, 
is greater than t - 

In Crelle's Journal' 1 TchebychefE proves Poisson's Theorem 
directly by a method similar to his general method, and also 
obtains several supplementary results such as the following : 

I. If the chances of an event E in p consecutive trials are 
PiPz - Pn respectively, and their sum is s 9 the probability that 
E will occur at least m times is less than 

^_ s y-m+i 

2(m-s)V ^ \fju 

provided that m>$ + I ; 

II. and the probability that E will not occur more than n times 
is less than 

fjb-n \n) 

provided that n< s - 1. 

III. Hence the probability that E will occur less than m times 
and more than n is greater than 


15. Tchebycheff's methods have been set out and his results 
admirably extended by A. A. MarkofE. 2 And some develop- 

1 Vol. 33 (1846), Demonstration elementaire ffune proposition gln&dle de la 
theorie des probability. 

a The reader is referred to MarkoiFs WaJirscheirilichkeitsrechnung, and par- 
ticularly to p. 67, for a striking development, along mathematical lines, of 


ments along, the same lines by Tschuprow (" Zur Theorie der 
Stabilitat statistischer Reihen," Skandinavisk Altiuarietidskrift, 
1919) have convinced me that Tchebycheffs discovery is far 
more than a technical device for solving a special problem, and 
points the way to the fundamental method for attacking these 
questions on the mathematical side. The Laplacian mathe- 
matics, although it still holds the field in most text-books, is 
really obsolete, and ought to be replaced by the very beautiful 
work which we owe to these three Russians. 

16. There is one other investigation relating to Bernoulli's 
Theorem which deserves remark. I have already pointed out, 
in 2, that the dispersion about the most probable value, even 
when the conditions for the applicability of Bernoulli's Theorem 
in its non-approximate form are strictly fulfilled, is unsym- 
metrical. The fact, that the usual approximation for the prob- 
ability of a divergence h from the most probable number of 
occurrences (the notation is that of 2 above) takes the form 

, which is the same for + h as for - h, has led 

to this want of symmetry being very generally overlooked ; 
and it is not uncommon to assume that the probability of a 
given divergence less than pm is equal to that of the same diverg- 
ence in excess of pm, and, in general, that the probability of 
the frequency's exceeding pm in a set of m trials is equal to that 
of its falling short of ym. 

That this is not strictly the case is obvious. If a die is cast 
60 times, the most probable number of appearances of the ace 
is 10 ; but the ace is more likely to appear 9 times than 11 times ; 
and much more likely (about 5 times as likely) not to appear at 
all than to appear exactly 20 times. That this must be so will 
be clear to the reader (without his requiring to trouble himself 
with the algebra), when he reflects that the ace cannot appear 
less often than not at all, whereas it may well appear more than 
20 times, so that the smallness of the possible divergence in 
defect from the most probable value 10, as compared with the 
possible divergence in excess, must be made up for by the greater 

TchebychefPs leading idea. Further references to later memoirs, which, being 
in the Russian language, are inaccessible to me, will be found in the Biblio- 


frequency of any given defection as compared with the corre- 
sponding excess. Thus the actual frequency in a series of trials 
of an event, of which the probability at each trial is less than J, 
is likely to fall short of its most probable value more often than 
it exceeds it. What is in fact true is that the mathematical 
expectation of deficiency is equal to the mathematical expecta- 
tion of excess, i.e. that the sum of the possible deficiencies each 
multiplied by its probability is equal to the sum of the possible 
excesses each multiplied by its probability. 

The actual measurement of this want of symmetry and the 
determination of the conditions, in which it can be safely 
neglected, involves laborious mathematics, of which I am only 
acquainted with one direct investigation, that published in the 
Proceedings of the London Mathematical Society by Mr. T. 0. 
Simmons. 1 

For the details of the proof I must refer the reader to Mr. 
Simmons's article. His principal theorem 2 is as follows : If 

- - is the probability of the event at each trial and n(a + 1) the 

number of trials, n and a being integers, 3 the probability that the 
frequency of occurrence will fall short of n is always greater than 
the probability that it will exceed n ; the difference between the 
two probabilities being a maximum when n = l, constantly 

diminishing as n increases, lying always between - - times the 

o a -f- 1 

. , , / * i Y (tt+1) A la ^ .- 

greatest term in - + -- - and rt times the 

B \a + l 

1 " A New Theorem in Probability." Mr. Simmons claimed novelty for 
his investigation, and so far as I know this claim is justified , but recent 
investigations obtaining closer approximations to Bernoulli's Theorem by moans 
of the Method of Moments are essentially directed towards the same problem. 

A somewhat analogous point has, however, been raised by .Professor Pearson 
in his article (Phil Mag., 1907) on " The Influence of Past Experience on Future 
Expectation." He brings out an exactly similar want of symmetry in the 
probabilities of the various possible frequencies about the most probable fre- 
quency, when the calculation is based, not on Bernoulli's Theorem as in Mr. 
Simmons' s investigation, but on Laplace's rule of succession (see next chapter). 
The want of symmetry has also been pointed out by Professor Lexis (Abhand- 
lungen, p. 120). 

2 I am not giving his own enunciation of it. 

8 Mr. Simmons does not seem to have been able to remove this restriction 
on the generality of Ms theorem, but there does not seem much reason to doubt 
that it can be removed. 



PT. V 

fa 1 

greatest term in -+ i- 
a -M 

<+ 1 X a + 1 ) 

, and being approxi- 

mately equal, when n is very large, to - 

The following table gives the value of the excess A of the 
probability of a frequency less than pm over the probability of 
a frequency greater than pm for various values of p the prob- 
ability and m the number of trials p = -, m = n(a + l) L as 
calculated by Mr. Simmons : 












































Thus unless not only m but mp also is large the want of symmetry 
is likely to be appreciable. Thus it is easily found that in 100 

sets of 4 trials each, where p = -, the actual frequency is likely to 
exceed the most probable 26 times and to fall short of it 31 times ; 
and in 100 sets of 10 trials each, where p = , to exceed 26 times 

and to fall short 34 times. 

Mr. Simmons was first directed to this investigation through 


noticing in the examination of sets of random digits that " each 
digit presented itself, with unexpected frequency, less than of 

the number of times. For instance, in 100 sets of 150 digits each, 
I found that a digit presented itself in a set more frequently under 
15 times than over 15 times ; similarly in the case of 80 sets each 
of 250 digits, and also in other aggregations." Its possible 
bearing on such experiments with dice and roulette, as are 
described at the end of this chapter, is clear. But apart from 
these artificial experiments, it is sometimes worth the statis- 
tician's while to bear in mind this appreciable want of symmetry 
in the distribution about the mode or most probable value in 
many even of those cases in which Bernoullian conditions are 
strictly fulfilled. 

17. I will conclude this chapter by an account of some of the 
attempts which have been made to verify d posteriori the con- 
clusions of Bernoulli's Theorem. These attempts are nearly 
useless, first, because we can seldom be certain d priori that the 
conditions assumed in Bernoulli's Theorem are fulfilled, and, 
secondly, because the theorem predicts not what will happen 
but only what is, on certain evidence, likely to happen. Thus 
even where our results do not verify Bernoulli's Theorem, the 
theorem is not thereby discredited. The results have bearing 
on the conditions in which the experiments took place, rather 
than upon the truth of the theorem. In spite, therefore, of the 
not unimportant place which these attempts have in the history 
of probability, their scientific value is very small. I record them, 
because they have a good deal of historical and psychological 
interest, and because they satisfy a certain idle curiosity from 
which few students of probability are altogether free. 1 

18. The data for these investigations have been principally 
drawn from four sources coin-tossing, the throw of dice, lotteries, 
and roulette ; for in such cases as these the conditions for 
Bernoulli's Theorem seem to be fulfilled most nearly. The earliest 
recorded experiment was carried out by Bufion, 2 who, assisted 

1 Mr. Yule (Introduction to Statistics, p. 264) recommends its indulgence : 
" The student is strongly recommended to carry out a few series of such ex- 
periments personally, in order to acquire confidence in the use of the theory.*" 
Mr. Yule himself has indulged moderately. 

* Eseai d'arithmetigue morale (see Bibliography), published 1777, said to 
have been composed about 1760. 


by a child tossing a coin into the air, played 2048 partis of the 
Petersburg game, in which a coin is thrown successively until 
the parti is brought to an end by the appearance of heads. The 
same experiment was repeated by a young pupil of De Morgan's 
6 for his own satisfaction/ 1 In Buffon's trials there were 1992 
tails to 2048 heads ; in Mr. H.'s (De Morgan's pupil) 2044 tails to 
2048 heads. A further experiment, due to Buffon's example, 
was carried out by Quetelet 2 in 1837. He drew 4096 balls from 
an urn, replacing them each time, and recorded the result at 
different stages, in order to show that the precision of the result 
tended to increase with the number of the experiments. He 
drew altogether 2066 white balls and 2030 black balls. Following 
in this same tradition is the experiment of "Jevons, 3 who made 
2048 throws of ten coins at a time, recording the proportion of 
heads at each throw and the proportion of heads altogether. In 
the whole number of 20,480 single throws, he obtained heads 
10,353 times. More recently Weldon 4 threw twelve dice 4096 
times, recording the proportion of dice at each throw which 
showed a number greater than three. 

All these experiments, however, are thrown completely into 
the shade by the enormously extensive investigations of the Swiss 
astronomer Wolf, the earliest of which were published in 1850 
and the latest in 1893. 5 In his first set of experiments Wolf 
completed 1000 sets of tosses with two dice, each set continuing 
until every one of the 21 possible combinations had occurred at 
least once. This involved altogether 97,899 tosses, and he then 
completed a total of 100,000. These data enabled him to work 
out a great number of calculations, of which Czuber quotes the 
following, namely a proportion of -83533 of unlike pairs, as against 

the theoretical value -83333, i.e. -. In his second set of experi- 

1 formal Logic, p. 185, published 1S47. De Morgan gives Buffon's results, 
as well as his pupil's, in full. Buffon's results are also investigated "by Poisson, 
Kecherches, pp. 132-135. 

3 Letters on the Theory of Probabilities (Eng. trans.), p. 37. 

3 Principles of Science (2nd ed.), p. 208. 

4 Quoted by Edgeworth, "Law of Error" (Ency. Brit. 10th ed.), and by 
Yule, Introduction to Statistics, p. 254. 

6 See Bibliography. Of the earliest of these investigations I have no first- 
hand knowledge and have relied upon the account given by Czuber, Zoc. cit. 
vol. i. p. 149. For a general account of empirical verifications of Bernoulli's 
Theorem reference may be made to Czuber, Waha-scheinlichkeitsrechnung, vol. i. 
pp. 139-152, and Czuber, EntwicTsUng der WahrscheinlicTikeitetlieorie, pp. 88-91. 


ments Wolf used two dice, one white and one red (in the first set 
the dice were indistinguishable), and completed 20,000 tosses, the 
details of each result being recorded in the Vierteljahrsschrift der 
Naturforsckenden Gesellschaft in Zurich. He studied particularly 
the number of sequences with each die, and the relative frequency 
of each, of the 36 possible combinations of the two dice. The 
sequences were somewhat fewer than they ought to have been, 
and the relative frequency of the different combinations very 
different indeed from what theory would predict. 1 The ex- 
planation of this is easily found ; for the records of the relative 
frequency of each face show that the dice must have been very 
irregular, the six face of the white die, for example, falling 38 
per cent more often than the four face of the same die. This, 
then, is the sole conclusion of these immensely laborious experi- 
inents, that Wolf's dice were very ill made. Indeed the ex- 
periments could have had no bearing except upon the accuracy 
of his dice. But ten years later Wolf embarked upon one more 
series of experiments, using four distinguishable dice, white, 
yellow, red, and blue, and tossing this set of foux 10,000 times. 
Wolf recorded altogether, therefore, in the course of his life 
280,000 results of tossing individual dice. It is not clear that 
Wolf had any well-defined object in view in making these 
records, which are published in curious conjunction with various 
astronomical results, and they afford a wonderful example of the 
pure love of experiment and observation. 2 

19. Another series of calculations have been based upon the 
ready-made data provided by the published results of lotteries 
and roulette. 3 

1 Czuber quotes the principal results (loc. cit. vol. i. pp. 149-151). The 
frequencies of only 4, instead of 18, out of the 36 combinations lay within the 
probable limits, and the standard deviation was 76-8 instead of 23-2. 

2 The latest experiment of the kind, of which I am aware, is that of Otto 
Meissner (" Wurtelversuche," Zeitschrifi far MatJi. und Phys. vol. 62 (1913), pp. 
149-156), who recorded 24 series of 180 throws each with four distinguishable 

3 For the publication of such returns there has always been a sufficient 
demand on the part of gamblers. An Almanack romain sur la loterie royale de 
Frame was published at Paris in 1830, which contained all the drawings of the 
French lottery (two or three a month) from 1758 to 1830. Players at Monte 
Carlo are provided with cards and pins with which to record the results of 
successive coups, and the results at the tables are regularly published in Le 
Monaco. Gamblers study these returns on account of the belief, which they 
usually hold, that as the number of cases is increased the absolute deviation from 
the most probable proportion becomes less, whereas at the best Bernoulli's 


Czuber 1 has made calculations based on the lotteries 
of Prague (2854 drawings) and Briinn (2703 drawings) between 
the years 1754 and 1886, in which the actual results agree 
very well with theoretical predictions. Fechner 2 employed the 
lists of the ten State lotteries of Saxony between the years 1843 
and 1852. Of a rather more interesting character are Professor 
Earl Pearson's investigations 3 into the results of Monte Carlo 
Roulette as recorded in Le Monaco in the course of eight weeks. 
Applying Bernoulli's Theorem, on the hypothesis of the equi- 
probability of all the compartments throughout the investigation, 
he found that the actually recorded proportions of red and black 
were not unexpected, but that alternations and long runs were 
so much in excess that, on the assumption of the exact accuracy 
of the tables, the d priori odds were at least a thousand millions 
to one against some of the recorded deviations. Professor 
Pearson concluded, therefore, that Monte Carlo Roulette is not 
objectively a game of chance in the sense that the tables on which 
it is played are absolutely devoid of bias. Here also, as in the 
case of Wolf's dice, the conclusion is solely relevant, not to the 
theory or philosophy of Chance, but to the material shapes of 
the tools of the experiment. 

Professor Pearson's investigations into Roulette, which dealt 
with 33,000 Monte Carlo coups, have been overshadowed, just 

Theorem shows that the proportionate deviation decreases while tho absolute 
deviation increases. Of. Houdin's Les Trickeries des Qrecs devoiUes : " In a 
game of chance, the oftener the same combination has occurred in succession, the 
nearer we are to the certainty that it will not recur at the next cast or turn-up. 
This is the most elementary of the theories on probabilities ; it is termed the 
maturity of the chances" Laplace (Essai philosophique, p. 142) quotes an 
amusing instance of the same belief not drawn from the annals of gambling : 
" J'ai vu des hommes desirant ardenunent d' avoir un fils, n'apprendre qu'avec 
peiue les nadssances des gargons dans le mois ou ils aUaient devenir peres. 
S'imaginant que le rapport de ces naissances a celles des filles devait etre le 
meme a la fin de ehaque mois, ils jugaient que les gargons deja ne"s rendaient 
plus probables les naissances prochaines des filles." 

^ The literature of gambling is very extensive, but, so far as J am acquainted 
with it, excessively lacking in variety, the maturity of the chances and the 
martingale continually recurring in one form or another. The curious reader 
will find tolerable accounts of such topics in Proctor's Chance and Luck, and 
Sir Hiram Maxim's Monte Carlo Facts and Fallacies. 

1 Zum Gesetz der grossen Zahlen. The results are summarised in his Wdhr- 
scheirilichkeitsrechnitnff> voL i. p- 139. 

a Kottektivmasslehre, p. 229. These results also are summarised by Czuber, 
loc. cit. 

3 The Chances of Death, vol. L 



as all other tosses of coins and dice Lave been outdone by Wolf, 
by Dr. Karl Marbe, 1 who has examined 80,000 coups from Monte 
Carlo and elsewhere. Dr. Marbe arrived at exactly opposite 
conclusions ; for he claims to have shown that long runs, so far 
from being in excess, were greatly in defect. Dr. Marbe intro- 
duces this experimental result in support of his thesis that the 
world is so constituted that long runs do not as a matter of fact 
occur in it. 2 Not merely are long runs very improbable. They 
do not, according to him, occur at all. But we may doubt 
whether roulette can tell us very much either of the laws of logic 
or of the constitution of the universe. 

Dr. Marbe's main thesis is identical, as he himself recognises, 
with one of the heterodox contentions of D'Alembert. 3 But this 
principle of variety, precisely opposite to the usual principle of 
Induction, can have no claim to be accepted d priori and, as a 
general principle, there is no adequate evidence to support it from 
experience. Its origin is to be found, perhaps, in the fact that 

1 Naturphilosophische Untersuchungen zur WahrscheirilichJceitstheorie. 

2 Dr. Marbe's monograph has given rise in Germany to a good deal of dis- 
cussion, not directed towards showing what a preposterous method this is for 
demonstrating a natural law, but because the experimental result itself does not 
really follow from the data and is due to a somewhat subtle error in Marbe's 
reasoning, by which he has been led into an incorrect calculation of the probable 
proportions d priori of the various sequences. The problem is discussed by 
Von Bortkiewicz, Bromse, Bruns, Grimsehl, and Grunbaum (for exact references 
to these see the Bibliography), and by Lexis (Abhandlungen, pp. 222-226) and 
Ozuber (WaTvrscfoinlichkeiterecJinung, vol. i. pp. 144-149). Largely as a result 
of this controversy, Von Bortkiewicz has lately devoted a complete treatise 
(Die Iterationeri) to the mathematics of * runs.' Dr. Marbe has been given 
far more attention by his colleagues in Germany than he conceivably deserves. 

8 D' Alembert's principal contributions to Probability are most accessible in 
the volumes of his Opuscules matMmatiguea (1761). Works on Probability 
usually contain some reference to D'Alembert, but his sceptical opinions, re- 
jected rather than answered by the orthodox school of Laplace, have not always 
received full justice. D'Alembert has three main contentions to which in his 
various papers he constantly recurs : 

(1) That a probability very small mathematically is really zero ; 

(2) That the probabilities of two successive throws with a die are not 
independent ; 

(3) That 'mathematical expectation* is not properly measured by the 
product of the probability and the prize. 

The first and third of these were partly advanced in explanation of the 
Petersburg paradox (see p. 316). The second is connected with the first, and 
was also used to support his incorrect evaluation of the probability of heads 
twice running ; but D'Alembert, in spite of many of his results being wrong, 
does not altogether deserve the ridicule which he has suffered at the hands of 
writers, who accepted without sceptical doubts the hardly less incorrect con- 
clusions of the orthodox theory of that time. 


in a certain class of cases, especially where conscious human 
agency comes in, it may contain some element of truth. The 
fact of an act's having been done in a particular way once may 
be a special reason for thinking that it will not be performed on 
the nest occasion in precisely the same manner. Thus in many 
so-called random events some slight degree of causal and material 
dependence between successive occurrences may, nevertheless, 
exist. In these cases e runs ' may be fewer and shorter than those 
which we should predict, if a complete absence of such dependence 
is assumed. If, for example, a pack of cards be dealt, collected, 
and shuffled, to the extent that card-players do as a rule shuffle, 
there may be a greater presumption against the second hand's 
being identical with the first than against any other particular 
distribution. In the case of croupiers long experience might 
possibly suggest some psychological generalisation, that they 
are very mechanical, giving an excess of numbers belonging to a 
particular section of the wheel, or, on the other hand, that when 
a croupier sees a run beginning, he tends to vary his spin more than 
usual, thus bringing runs to an end sooner than he ought. 1 At any 
rate, it is worth emphasising once more that from such experi- 
ments as these this is the only kind of knowledge which we can 
hope to obtain, knowledge of the material construction of a 
die or of the psychology of a croupier. 

1 A good roulette table is, however, so delicate an instrument that no prob- 
able degree of regularity of habit on the part of the spinner could bo sufficient 
to produce regularity in the result. 



Utilissima est aestimatio probabilitatum, quanquam in exemplis juridicis 
politicisque plerumque non tarn subtili calculo opus est, quam aocurata 
omnium circumstantiarum enumeratione. LEIBNIZ. 

1. IN the preceding chapter we have assumed that the probability 
of an event at each of a series of trials is given, and have considered 
how to infer from this the probabilities of the various possible 
frequencies of the event over the whole series, without discussing 
in detail by what method the initial probability had been deter- 
mined. In statistical inquiries it is generally the case that this 
initial probability is based, not upon the Principle of In- 
difference, but upon the statistical frequencies of similar events 
which have been observed previously. In this chapter, therefore, 
we must commence the complementary part of our inquiry, 
namely, into the method of deriving a measure of probability 
from an observed statistical frequency. 

I do not myself believe that there is any direct and simple 
method by which we can make the transition from an observed 
numerical frequency to a numerical measure of probability. 
The problem, as I view it, is part of the general problem of found- 
ing judgments of probability upon experience, and can only be 
dealt with by the general methods of induction expounded in 
Part HE. The nature of the problem precludes any other method, 
and direct mathematical devices can all be shown to depend 
upon insupportable assumptions. In the next chapters we will 
consider the applicability of general inductive methods to this 
problem, and in this we will endeavour to discredit the mathe- 
matical charlatanry by which, for a hundred years past, the basis 
of theoretical statistics has been greatly undermined, 



2. Two direct methods have been commonly employed, 
theoretically inconsistent with one another, though not in every 
case noticeably discrepant in practice. The first and simplest of 
these may be termed the Inversion of Bernoulli's Theorem, and 
the other Laplace's Rule of Succession. 

The earliest discussion of this problem is to be found in the 
Correspondence of Leibniz and Jac. Bernoulli, 1 and its true 
nature cannot be better indicated than by some account of the 
manner in which it presented itself to these very illustrious 
philosophers. The problem is tentatively proposed by Bernoulli 
in a letter addressed to Leibniz in the year 1703. We can deter- 
mine from d priori considerations, he points out, by how much it 
is more probable that we shall throw 7 rather than 8 with two dice, 
but we cannot determine by such means the probability that a 
young man of twenty will outlive an old man of sixty. Yet is it 
not possible that we might obtain this knowledge d posteriori 
from the observation of a great number of similar couples, each 
consisting of an old man and a young man ? Suppose that the 
young man was the survivor in 1000 cases and the old man in 500 
cases, might we not conclude that the young man is twice as likely 
as the old man to be the survivor ? For the most ignorant 
persons seem to reason in this way by a sort of natural instinct, 
and feel that the risk of error is diminished as the number of 
observations is increased. Might not the solution tend asymp- 
totically to some determinate degree of probability with the 
increase of observations ? Nesdo, Vir Amplisswne, cm specular 
tiowfous istis soliditatis aliquid inesse Tibi videatur. 

Leibniz's reply goes to the root of the difficulty. The calcula- 
tion of probabilities is of the utmost value, he says, but in statisti- 
cal inquiries there is need not so much of mathematical subtlety 
as of a precise statement of all the circumstances. The possible 
contingencies are too numerous to be covered by a finite number 
of experiments, and exact calculation is, therefore, out of the 
question. Although nature has her habits, due to the recurrence 
of causes, they are general, not invariable. Yet empirical calcula- 
tion, although it is inexact, may be adequate in affairs of practice. 2 

1 For the exact references see Bibliography. 

a Leibniz's actual expressions (in a letter to Bernoulli, December 3, 1703) are 
as follows : Utilissima est aestimatio probabilitatum, quanquam in exemplis 
juridicis politicisque plerumque non tarn subtili calculo opus est, quam accurata 
pmnium circumstantiarum enumeratione. Cum empirice aestimamus proba- 


Bernoulli in Ms answer fell back upon the analogy of balls 
drawn from an urn, and maintained that without estimating 
each separate contingency we might determine within narrow 
limits the proportion favouring each alternative. If the true 
proportion were 2 : 1, we might estimate it with moral certainty 
d posteriori as lying between 201 : 100 and 199 : 100. " Certus 
sum," he concluded the controversy, " Tibi placituram demonstra- 
tionem, cum publicavero." But whether he was impressed by 
the just caution of Leibniz, or whether death intercepted him, 
he advances matters no further in the Ars Gonjectandi. After 
dealing with some of Leibniz's objections I and seeming to 
promise some mode of estimating probabilities d posteriori by an 
inversion of his theorem, he proves the direct theorem only and 
the book is suddenly at an end. 

3. In dealing with the correspondence of Leibniz and Ber- 
noulli, I have not been mainly influenced by the historical interest 
of it. The view of Leibniz, dwelling mainly on considerations 
of analogy, and demanding " not so much mathematical subtlety 
as a precise statement of all the circumstances," is, substantially, 
the view which will be supported in the following chapters. 
The desire of Bernoulli for an exact formula, which would derive 
from the numerical frequency of the experimental results a 
numerical measure of their probability, preludes the exact 
formulas of later and less cautious mathematicians, which will be 
examined immediately. 

4. During the greater part of the eighteenth century there is 
no trace, I think, of the explicit use of the Inversion of Bernoulli's 
Theorem. The investigations carried out by D'Alembert, Daniel 
Bernoulli, and others relied upon the type of argument examined 
in Chapter XXV. They showed, that is to say, that certain 
observed series of events would have been very improbable, if 
we had supposed independence between some two factors or if 

bilitates per experimenta successuum, cjtiaeris an ea via tandem aestimatio 
perfeote obtineri possit. Idque a Te repertum scribis. Dimcultas in eo mihi 
inesse videtur, quod contingentia sen quae infinitis pendent ciroumstantiis, per 
finita experimenta determinari non possunt ; natura qttidem suas habet oonsue- 
tudines, natas ex reditu causarum, sed non nisi d>s M rb TroXtf. Novi morbi 
inundant subinde kumanum genus, quodsi ergo de mortibus quotounque ex- 
perimenta f eceris, non ideo naturae rerum limites posuisti, ut pro futuro variare 
non possit. Etsi autem empirice non posset haberi perfeota aestimatio, non 
ideo mimis empirica aestimatio in praxi utilis et sumciens f oret. 

1 The relevant passages are on pp. 224-227 of the Ars Gonjectandi. 



some occurrence had been assumed to be as likely as not, and they 
inferred from this that there was in fact a measure of dependence 
or that the occurrence had probability in its favour. But they 
did not endeavour to pass from the observed frequency of occur- 
rence to an exact measure of the probability. With the advent 
of Laplace more ambitious methods took the field. 

Laplace began by assuming without proof a direct inversion 
of Bernoulli's Theorem. Bernoulli's Theorem, in the form in 
which Laplace proved it, states that, if p is the probability a 

priori, there is a probability P that the proportion of times ------ 

of the event's occurrence in p,(=m + ri) trials will lie between 

, where P = -= -*dt + =-e-*. The in- 

version of the theorem, which he assumes without proof, 
states that, if the event is observed to happen m times 
in fj, trials, there is a probability P that the probability 

of the event *p will lie between <y / 5-, where 

H> \l /j? 

2 f Y 1 

P = T= I e~^H ^"y 2 . The same result is ako given 

by Poisson. 1 Thus, given the frequency of occurrence in p 
trials, these writers infer the probability of occurrence at 
subsequent trials within certain limits, just as, given the 
a priori probability, Bernoulli's Theorem would enable them 
to predict the frequency of occurrence in JUL trials within corre- 
sponding limits. 

1 For an account of the treatments of this topic both by Laplace and by 
Poisson, see Todlranter's History, pp. 554-557. Both of them also obtain a 
formula slightly different from that given above by a method analogous to the 
first part of the proof of Laplace's Rule of Succession ; i.e. by an application of 
the inverse principle of probability to the assumption that the probability of 
the probability's lying within any interval is proportional to the length of the 
interval. This discrepancy has given rise to some discussion. See Todhunter, 
loc. cit. ; De Morgan, On a Question in the Theory of Probabilities ; Monro, On the 
Inversion of Bernoulli's Theorem in Probabilities ; and Czuber, Entwickfang, 
pp. 83, 84. But this is not the important distinction between the two mathe- 
matical methods by which this question has been approached, and this minor 
point, which is of historical interest mainly, I forbear to enter into. 


If the number of trials is at all numerous, these limits are 
narrow and the purport of the inversion of Bernoulli's Theorem 
may therefore be put briefly as follows. By the direct theorem, 
if p measures the probability, p also measures the most probable 

value of the frequency ; by the inversion of the theorem, if 

measures the frequency, also measures the most probable 

^ J m+n r 

value of the probability. The simplicity of the process has re- 
commended it, since the time of Laplace, to a great number of 
writers. Czuber's argument, criticised on p. 351, with reference 
to the proportions of male and female births in Austria, is based 
upon an unqualified use of it. But examples abound throughout 
the literature of the subject, in which the theorem is employed in 
circumstances of greater or less validity. 

The theorem was originally given without proof, and is indeed 
incapable of it, unless some illegitimate assumption has been 
introduced. But, apart from this, there are some obvious objec- 
tions. We have seen in the preceding chapter that Bernoulli's 
Theorem itself cannot be applied to all kinds of data indiscrimin- 
ately, but only when certain rather stringent conditions are ful- 
filled. Corresponding conditions are required equally for the 
inversion of the theorem, and it cannot possibly be inferred from 
a statement of the number of trials and the frequency of occur- 
rence merely, that these have been satisfied. We must know, 
for instance, that the examined instances are similar in the main 
relevant particulars, both to one another and to the unexamined 
instances to which we intend our conclusion to be applicable. 
An unanalysed statement of frequency cannot tell us this. 

This method of passing from statistical frequencies to prob- 
abilities is not, however, like the method to be discussed in a 
moment, radically false. With due qualifications it has its place 
in the solution of this problem. The conditions in which an 
inversion of Bernoulli's Theorem is legitimate will be elucidated 
in Chapter XXXI. In the meantime we will pass on to Laplace's 
second method, which is more powerful than the first and has 
obtained a wider currency. The more extreme applications of 
it are no longer ventured upon, but the theory which underlies 
it is still widely adopted, especially by French writers upon 
probability, and seldom repudiated. 


5. The formula in question, which Venn * has called the Rule 
of Succession, declares that, if we know no more than that an 
event has occurred m times and failed n times under given con- 
ditions, then the probability of its occurrence when those con- 
ditions are next fulfilled is ^. It is necessary, however, 

m + n + 4 

before we examine the proof of this formula, to discuss in detail 
the reasoning which leads up to it. 

This preliminary reasoning involves the Laplacian theory of 
e unknown probabilities.' The postulate, upon which it depends, 
is introduced to supplement the Principle of Indifference, and 
is in fact the extension of this principle from the probabilities 
of arguments, when we know nothing about the arguments, to the 
probabilities that the probabilities of arguments have certain 
values, when we know nothing about the probabilities. Laplace's 
enunciation is as follows : " Quand la probabilite d'un 6venement 
simple est inconnue, on peut lui supposer egalement toutes les 
valeurs depuis zero jusqu'a Tunite. La probabilite de chacune 
de ces hypotheses tiree de Tev^nement observe est . . . une 
fraction dont le numerateur est la probabilite de T6venement dans 
cette hypothese, et dont le denominateur est la somme des pro- 
babilites semblables relatives a toutes les hypotheses. . . ." 2 

Thus when the probability of an event is unknown, we may 
suppose all possible values of the probability between and 1 to 
be equally likely d priori. The probability, after the event has 

occurred, that the probability d priori was - (say), is measured 

by a fraction of which - is the numerator and the sums of all the 
J r 

possible d priori values the denominator. The origin of this rule 
is evident. If we consider the problem in which a ball is drawn 
from a bag containing an infinite number of black and white balls 
in unknown proportions, we have hypotheses, corresponding to 
each of the possible constitutions of the bag, the assumption of 
which yields in turn every value between and 1 as the d priori 
probability of drawing a white ball. If we could assume that 
these constitutions are equally probable d priori, we should 
obtain probabilities for each of them d posteriori according to 
Laplace's rule. 

1 Logic of Chance, p, 190. Ssaai philonophique, p. 10. 


On the analogy of this Laplace assumes in general that, where 
everything is -unknown, we may suppose an infinite number of 
possibilities, each of which is equally likely, and each of which, 
leads to the event in question with a different degree of probability, 
so that for every value between and 1 there is one and only one 
hypothetical constitution of things, the assumption of which 
invests the event with a probability of that value. 

6. It might be an almost sufficient criticism of the above to 
point out that these assumptions are entirely baseless. But the 
theory has taken so important a place in the development of 
probability that it deserves a detailed treatment. 

What, in the first place, does Laplace mean by an unknown 
probability ? He does not mean a probability, whose value is in 
fact unknown to us, because we are unable to draw conclusions 
which could be drawn from the data ; and he seems to apply the 
term to any probability whose value, according to the argument 
of Chapter III., is numerically indeterminate. Thus he assumes 
that every probability has a numerical value and that, in those 
cases where there seems to be no numerical value, this value is 
not non-existent but unknown ; and he proceeds to argue that 
where the numerical value is unknown, or as I should say where 
there is no such value, every value between and 1 is equally 
probable. With the possible interpretations of the term ' un- 
known probability,' and with the theory that every probability 
can be measured by one of the real numbers between and 1, 
I have dealt, as carefully as I can, m Chapter IIL If the view 
taken there is correct, Laplace's theory breaks down immediately. 
But even if we were to answer these questions, not as they have 
been answered in Chapter III., but in a manner favourable to 
Laplace's theory, it remains doubtful whether we could legitim- 
ately attribute a value to the probability of an unknown prob- 
ability's having such and such a value. If a probability is 
unknown, surely the probability, relative to the same evidence, 
that this probability has a given value, is also unknown ; and we 
are involved in an infinite regress. 

7. This point leads on to the second objection ; Laplace's 
theory requires the employment of both of two inconsistent 
methods. Let us consider a number of alternatives a l3 a 2 , etc., 
having probabilities p v p 2 , etc. ; if we do not know anything 
about %, we do not know the value of its probability y l9 and we 


must consider tlie various possible values of p l3 namely 6 l5 6 2 , etc., 
the probabilities of these possible values being q l9 q& etc. respect- 
ively. There is no reason why this process should ever stop. 
For as we do not know anything about 6 19 we do not know the 
value of its probability q v and we must consider the various 
possible values of q v namely c^ c 2 , etc., the probabilities of these 
possible values being r^ r 2 , etc. respectively ; and so on. This 
method consists in supposing that, when we do not know anything 
about an alternative, we must consider all the possible values of 
the probability of the alternative ; these possible values can form 
in their turn a set of alternatives, and so on. But this method 
by itself can lead to no final conclusion. Laplace superimposes 
on it, therefore, his other method of determining the probabilities 
of alternatives about which we know nothing, namely, the 
Principle of Indifference. According to this method, when 
we know nothing about a set of alternatives, we suppose the 
probabilities of each of them to be equal. In some parts of 
his writings and this is true also of most of his followers he 
applies this method from the beginning. If, that is to say, we 
know nothing about %, since a^ and its contradictory form a pair 
of exhaustive alternatives two in number, the probability of these 

alternatives is equal and each is ~. But in the reasoning which 


leads up to the Law of Succession he chooses to apply this method 
at the second stage, having used the other method at the first 
stage. If, that is to say, we know nothing about %, its prob- 
ability p-L may have any of the values b ly 6 2 , e ^ c - where ^ is any 
fraction between and 1 ; and, as we know nothing about the 
probabilities q l} j 2 , etc. of these alternatives 6 l9 6 2 , etc., we may 
by the Principle of Indifference suppose them to be equal. This 
account may seem rather confused ; but it is not easy to give 
a lucid account of so confused a doctrine. 

8. Turning aside from these considerations, let us examine 
the theory, for a moment, from another side. When we reach the 
Eule of Succession, it will be seen that the hypothetical d priori 
probabilities are treated as if they were possible causes of the 
event. It is assumed, that is to say, that the number of possible 
sets of antecedent conditions is proportional to the number of 
real numbers between and 1 ; and that these fall into equal 
groups, each group corresponding to one of the real numbers 


between and 1, this number measuring the degree of probability 
with which we could predict the event, if we knew that an ante- 
cedent condition belonging to that group was fulfilled. It is 
then assumed that all of these possible antecedent conditions are 
d priori equally likely. The argument has arisen by false analogy 
from th.e problem in which a ball is drawn from an urn containing 
an infinite number of black and white balls. But for the assump- 
tion that we have in general the kind of knowledge which is 
necessary about the possible antecedents, no reasonable founda- 
tion has been suggested. 

De Morgan endeavoured to deal with the difficulty in much 
the same way in the following passage : x " In determining the 
chance which exists (under known circumstances) for the happen- 
ing of an event a number of times which lies between certain 
limits, we are involved in a consideration of some difficulty, 
namely, the probability of a probability, or, as we have called it, 
the presumption of a probability. To make this idea more clear, 
remember that any state of probability may be immediately 
made the expression of the result of a set of circumstances, which 
being introduced into the question, the difficulty disappears. 
The WSrd presumption refers distinctly to an act of the mind, or a 
state of the mind, while in the word probability we feel disposed 
rather to think of the external arrangements on the knowledge 
of which the strength of our presumption ought to depend, than 
of the presumption itself/' The point of this explanation lies 
in the assumption that " any state of probability may be imme- 
diately made the expression of the result of a set of circumstances." 
It cannot be allowed that this is generally true ; 2 and even in 
those cases in which it is true we are thrown back on the d priori 
probabilities of the various sets of circumstances which freed not 
be, as De Morgan assumes, either equal or exhaustive alternatives. 

9. The proof of the Rule of Succession, which is based upon 
this theory of unknown probabilities, is, briefly, as follows : 

If x stands for the d priori probability of an event in given 
conditions, then the probability that the event will occur m 
times and fail n times in these conditions is # m (l - x) n . If, 
however, x is unknown, all values of it between and 

1 Cabinet Encyclopaedia, p. 87. 

2 For instance, it is not true even in the standard instance of balk drawn from 
an urn. containing black and white in unknown proportions, unless the^nuiaber 
of balls is infinite. 


1 are a priori equally probable. It follows from these two 
sets of considerations that, if tlie event has been observed 
to occur m times out of m+n, the probability d posteriori that 
x lies between x and x + dx is proportional to x m (l - x) n dx, 
and is equal, therefore, to Ax m (l -x) n dx where A is a constant. 
Since the event has in fact occurred, and since x must have 
one of its possible values, A is determined by the equation 


Hence the probability that the event will occur at the (m + n + l)th 
trial, when we know that it has occurred m times in m + n 
trials, is 

' o 

If we substitute the value of A found above, this is equal to 
m + 1 i 

The class of problem to which the theorem is supposed to 
apply is the following : There are certain conditions such that we 
are ignorant d priori as to whether they do or do not lead to the 
occurrence of a particular event ; on m out of m + n occasions, 
however, on which these conditions have been observed, the 
event has occurred ; what is the probability in the light of this 
experience that the event will occur on the next occasion ? The 

answer to all such problems is -. In the cases where 

m+n + 2 

^=0, i.e. when the event has invariably occurred, the formula 

1 The theorem is sometimes enunciated by contemporary writers in a much 
more guarded form, e.$. by Czuber, WahrscTieinUchkeitstrechnung, vol. i. p. 197, 
and by Bachelier, Calcul des probability p. 487. Bachelier, instead of assuming 
that the d priori probabilities of all possible values of the probability of the 
event are equal, writes &(y)dy as the d priori probability that tho probability is 
y, so that after m occurrences is m+n trials the probability that the probability 
lies between y and y + dy is J^J^^ H one ^ no idea of fl d 

priori, he suggests that the simplest hypothesis is to put w=l, which loads, as 
above, to Laplace's Law of Succession. He also proposes the hypothesis 
*(y) = a + 0$ + e&? + . . ., in which case the denominator is a series of Eulorian 
integrals. There is a discussion of the Law of Succession, and of the contra- 
ptions and paradoxes to which it leads, by E. T. Whittaker and others in 
U ^ Transactiom f the ^acuity of Actuaries in 


yields the result - -. In the case where the conditions have 


been observed once only and the event has occurred on that 


occasion, the result is -. If the conditions have never been met 


with at all, the probability of the event is -. And even in the 


case where on the only occasion on which the conditions were 

observed, the event did not occur, the probability is - 


Some of the flaws in this proof have been already explained. 
One minor objection may be pointed out in addition. It is 
assumed that, if # is the a priori probability of the event's happen- 
ing once, then x n is the d priori probability of its happening n 
times in succession, whereas by the theorem's own showing the 
knowledge that the event has happened once modifies the prob- 
ability of its happening a second time ; its successive occurrences 
are not, therefore, independent. If the d priori probability of the 

event is -, and if, after it has been observed once, the probability 

that it will occur a second time is -, then it follows that the d 

11 12 

priori probability of its occurring twice is not - x but - x -, 
j & 2 2 o 

i.e. - ; and in general the d priori probability of its happening 
. . /1V 1 l 

n times in succession is not ( - but ---- 

\2/ n + 1 

10. But refinements of disproof are hardly needed. The 
principle's conclusion is inconsistent with its premisses. We 
begin with the assumption that the d priori probability of an event, 
about which we have no information and no experience, is un- 
known, and that all values between and 1 are equally probable. 
We end with the conclusion that the d priori probability of 

such an event is -. It has been pointed out in 7 that this 

contradiction was latent, as soon as the Principle of Indifference 
was superimposed on the principle of unknown probabilities. 

The theorem's conclusions, moreover, are a reductio ad 
absurdum of the reasoning upon which it is based. Who could 
suppose that the probability of a purely hypothetical event, of 


whatever complexity, in favour of which no positive argument 
exists, the like of which has never been observed, and which has 
failed to occur on the one occasion on which the hypothetical 

conditions were fulfilled, is no less than - ? Or if we do suppose it, 

we are involved in contradictions, f or it is easy to imagine more 
than three incompatible events which satisfy these conditions. , 

11. The theorem was first suggested by the problem of the urn 
which contains black and white balls in unknown proportions : 
m white and n black balls have been successively drawn and 
replaced ; what is the probability that the next draw will yield 
a white ball ? It is supposed that all compositions of the urn are 
equally probable, and the proof then proceeds precisely as in the 
case of the more general rule of succession. The rule of succession 
has been, sometimes, directly deduced from the case of the urn, 
by assimilating the occurrence of the event to the drawing of a 
white ball and its non-occurrence to the drawing of a black ball. 

On the hypothesis that all compositions of the urn are equally 
probable, an hypothesis to which in general there is nothing corre- 
sponding, and on the further hypothesis that the number of balls 
is infinite, this solution is correct. 1 But the rule of succession 
does not apply, as it is easy to demonstrate, even to the case of 
balls drawn from an urn, if the number of balls is finite. 2 

12. If the Rule of Succession is to be adopted by adherents of 
the Frequency Theory of Probability, 3 it is necessary that they 
should make some modification in the preliminary reasoning on 
which it is based. By Dr. Venn, however, the rule has been 

1 This second condition is often omitted (e.g. Bertrand, Calcul des vroba- 
bilitls, p. 172). 

* The correct solution for the case of a finite number of balls, on the hypo- 
thesis that each possible ratio is equally likely, is as follows : The probability 
of a black ball at a further trial, after black balls have been successively with- 
drawn and replaced # times, is ^ ^ where there are n balls and s r represents 
the sum of the rth powers of thelurst n natural numbers. This reduces to 
|-j-g, the solution usually given, when n is infinite. More generally, if 
p black balls and q white balls have been drawn and replaced, the chance 

that the next ball will be black is - 

n r= 

3 See Chapter VHT. 


explicitly rejected on the ground that it does not accord with 
experience, 1 But Professor Karl Pearson, who accepts it, has 
made the necessary restatement, 2 and it will be worth while to 
examine the reasoning when it is put in this form. Professor 
Pearson's proof of the Eule of Succession is as follows : 

" I start, as most mathematical writers have done, with f the 
equal distribution of ignorance/ or I assume the truth of Bayes' 
Theorem. I hold this theorem not as rigidly demonstrated, but 
I think with Edgeworth 3 that the hypothesis of the equal dis- 
tribution of ignorance is, within the limits of practical life, justi- 
fied by our experience of statistical ratios, which d priori are 
unknown, i.e. such ratios do not tend to cluster markedly round 
any particular value. ' Chances ' lie between and 1, but our 
experience does not indicate any tendency of actual chances to 
cluster round any particular value in this range. The ultimate 
basis of the theory of statistics is thus not mathematical but 
observational. Those who do not accept the hypothesis of the 
equal distribution of ignorance and its justification in observation 
are compelled to produce definite evidence of the clustering of 
chances, or to drop all application of past experience to the judg- 
ment of probable future statistical ratios. . . . 

" Let the chance of a given event occurring be supposed to lie 
between x and x + dx, then if on n =p + q trials an event has been 
observed to occur p times and fail q times, the probability that 
the true chance lies between x and x + dx is, on the equal 
distribution of our ignorance, 

J o 

" This is Bayes 5 Theorem. . . . 4 

1 Logic of Chance, p. 197. 

2 " On the Influence of Past Experience on Future Experience on Future 
Expectation," PMl. Mag., 1907, pp. 365-378. The quotations given below are 
taken from this article. 

s This reference is, no doubt, to Edgeworth's " Philosophy of Chance " 
(Mind, 1884, p. 230), when he wrote : " The assumption that any probability- 
constant about which we know nothing in particular is as likely to have one value 
as another is grounded upon the rough but solid experience that such constants 
do, as a matter of fact, as often have one value as another." See also Chapter 
VII. 6, above. 

4 Professor Pearson's use of this title for the above formula is not, I think, 
historically correct. Bayes' Theorem is the Inverse Principle of Probability 
itself, and not this extension of it. 


"Now suppose that a second trial of m**r+s instances be 
made, then the probability that the given event will occur r times 
and fail s, is on the a priori chance being between x and x + dx 

and accordingly the total chance C r , whatever x may be of the 
event occurring r times in the second series, is 



\ X p (l 
J n 

This is, with a slight correction, Laplace's extension of Bayes 5 
Theorem." a 

13. This argument can be restated as follows. Of all the 
objects which satisfy cf>(x), let us suppose that a proportion p 
also satisfy f(x). In this case p measures the probability that 
any object, of which we know only that it is <, is in fact also /. 
Now if we do not know the value of p and have no relevant in- 
formation which bears upon it, we can assume d priori that all 
values of p between and 1 are equally likely. This assumption, 
which is termed the ' equal distribution of ignorance,' is justified 
by our experience of statistical ratios. Our experience, that is 
to say, leads us to suppose that of all the theories, which could be 
propounded, there are just as many which are always true as 
there are which are always false, just as many which are true once 
in fifty times as there are which are true once in three times, and 
so, on. Professor Pearson challenges those who do not accept 
this assumption to produce definite evidence to the contrary. 

The challenge is easily met. It would not be difficult to pro- 
duce 10,000 positive theories which are always false corresponding 
to every one which is always true, and 10,000 correlations of posi- 

1 The rest of the article is concerned with the determination of the probable 
error when Laplace's Rule of Succession is used not simply to yield the prob- 
ability of a single additional occurrence, but to predict the probable limits within 
which the frequency will lie in a considerable series of additional trials. Pro- 
fessor Pearson's method applies more rigorous methods of approximation to 
the fundamental formulae given above than have been sometimes used. As 
my main purpose in this chapter is to dispute the general validity of the funda- 
mental formulae, it is not worth while to consider these further developments 
here. If the validity of the fundamental formula were to be granted, Professor 
Pearson's methods of approximation would, I think, be satisfactory. 


tive qualities which hold less often than once in three times for 
every one we can name which holds more often than once in three 
times. And the converse is the case for negative theories and 
correlations between negative qualities ; for corresponding to 
every positive theory which is true there is a negative theory 
which is false, and so on. Thus experience, if it shows anything, 
shows that there is a very marked clustering of statistical ratios 
in the neighbourhoods of zero and unity, of those for positive 
theories and for correlations between positive qualities in the 
neighbourhood of zero, and of those for negative theories and for 
correlations between negative qualities in the neighbourhood of 
unity. Moreover, we are seldom in so complete a state of ignor- 
ance regarding the nature of the theory or correlation under 
investigation as not to know whether or not it is a positive theory 
or a correlation between positive qualities. In general, therefore, 
whenever our investigation is a practical one, experience, if it 
tells us anything, tells us not only that the statistical ratios cluster 
in the neighbourhood of zero and unity, but in which of these two 
neighbourhoods the ratio in this particular case is most likely 
d priori to be found. If we seek to discover what proportion of 
the population suffer from a certain disease, or have red hair, or 
are called Jones, it is preposterous to suppose that the proportion 
is as likely d priori to exceed as to fall short of (say) fifty per cent. 
As Professor Pearson applies this method to investigations where 
it is plain that the qualities involved are positive, he seems to 
maintain that experience shows that there are as many positive 
attributes which are shared by more than half of any population 
as there are which are shared by less than half. 

It is also worth while to point out that it is formally impossible 
that it should be true of all characters, simple and complex, that 
they are as likely to have any one frequency as any other. For let 
us take a character c which is compound of two characters a and 
b, between which there is no association, and let us suppose that 
a has a frequency x in the population in question and that b has 
a frequency y, so that, in the absence of association, the frequency 
z of c is equal to xy. Then it is easy to show that, if all values of 
x and y between and 1 are equally probable, all values of z 

between and 1 are not equally probable. For the value - 


is more probable than any other, and the possible values of 


2 become increasingly improbable as they differ more widely 
from - 

It may be added that the conclusions, which Professor 
Pearson himself derives from this method, provide a reductio 
ad dbsurdwm of the arguments upon which they rest. He con- 
siders, for example, the following problem : A sample of 100 of a 
population shows 10 per cent affected with a certain disease. 
What percentage may be reasonably expected in a second sample 
of 100 ? By approximation he reaches the conclusion that the 
percentage of the character in the second sample is as likely to 
fall inside as outside the limits, 7-85 and 13-71. Apart from the 
preceding criticisms of the reasoning upon which this depends, 
it does not seem reasonable upon general grounds that we should 
be able on so little evidence to reach so certain a conclusion. The 
argument does not require, for example, that we have any know- 
ledge of the manner in which the samples are chosen, of the 
positive and negative analogies between the individuals, or indeed 
anything at all beyond what is given in the above statement. 
The method is, in fact, much too powerful. It invests any posi- 
tive conclusion, which it is employed to support, with far too high 
a degree of probability. Indeed this is so foolish a theorem 
that to entertain it is discreditable. 

14. The Rule of Succession has played a very important part 
in the development of the theory of probability. It is true that 
it has been rejected by Boole 1 on the ground that the hypotheses 
on which it is based are arbitrary, by Venn 2 on the ground that it 
does not accord with experience, by Bertrand 3 because it is 
ridiculous, and doubtless by others also. But it has been very 
widely accepted, by De Morgan, 4 by Jevons, 5 by Lotee, 6 by 
Czuber, 7 and by Professor Pearson, 8 to name some representative 
writers of successive schools and periods. And, in any case, it 

1 Laws of TfouQht, p. 369. 2 Logic of Chance, p. 197. 

3 Cakul dee probabilites, p. 174. 

* Article in Cabinet Encyclopaedia, p. 64. 5 Principles of Science, p. 297. 

6 Logic, pp. 373, 374 ; Lotze propounds a " simple deduction " "as convin- 
cing'* to him "as the more obscure analysis, by which it is usually obtained." 
The proof is among the worst ever conceived, and may be commended to those 
who seek instances of the profound credulity of even considerable thinkers. 

7 Wanrscheinlichkeiterechnung, vol. i. p. 199, though, much more guardedly 
and with more qualifications than in the form discussed above. 

8 Loc. cit. 


is of interest as being one of the most characteristic results of a 
way of thinking in probability introduced by Laplace, and never 
thoroughly discarded to this day. Even amongst those writers 
who have rejected or avoided it, this rejection has been due 
more to a distrust of the particular applications of which the law 
is susceptible than to fundamental objections against almost 
every step and every presumption upon which its proof depends. 
Some of these particular applications have certainly been 
surprising. The law, as is evident, provides a numerical measure 
of the probability of any simple induction, provided only that our 
ignorance of its conditions is sufficiently complete, and, although, 
when the number of cases dealt with is small, its results are in- 
credible, there is, when the number dealt with is large, a certain 
plausibility in the results it gives. But even in these cases 
paradoxical conclusions are not far out of sight. When Laplace 
proves that, account being taken of the experience of the human 
race, the probability of the sun's rising to-morrow is 1,826,214 to 1, 
this large number may seem in a kind of way to represent our 
state of mind about the matter. But an ingenious German, 
Professor Bobek, 1 has pushed the argument a degree further, and 
proves by means of these same principles that the probability of 
the sun's rising every day for the next 4000 years, is not more, 
approximately, than two-thirds, a result less dear to our natural 

Lehrbuch der Wahrscheinlichkeitsrechnung, p. 208. 



1. I CONCLUDE, then, that the application of the mathematical 
methods, discussed in the preceding chapter, to the general 
problem of statistical inference is invalid. Our state of know- 
ledge about our material must be positive, not negative, before 
we can proceed to such definite conclusions as they purport to 
justify. To apply these methods to material, unanalysed in 
respect of the circumstances of its origin, and without reference 
to our general body of knowledge, merely on the basis of arith- 
metic and of those of the characteristics of our material with 
which the methods of descriptive statistics are competent to 
deal, can only lead to error and to delusion. 

But I go further than this in my opposition to them. Not 
only are they the children of loose thinking, and the parents of 
charlatanry. Even when they are employed by wise and com- 
petent hands, I doubt whether they represent the most fruitful 
form in which to apply technical and mathematical methods to 
statistical problems, except in a limited class of special cases. 
The methods associated with the names of Lexis, Von BortMewicz, 
and Tschuprow (of whom the last named forms a link, to some 
extent, between the two schools), which will be briefly described 
in the next chapter, seem to me to be much more clearly con- 
sonant with the principles of sound induction. 

2. Nevertheless it is natural to suppose that the fundamental 
ideas, from which these methods have sprung, are not wholly 
gars. It is reasonable to presume that, subject to suitable con- 
ditions and qualifications, an inversion of Bernoulli's Theorem 
must have validity. If we knew that our material could be 
likened to a game of chance, we might expect to infer chances 
from frequencies, with the same sort of confidence as that with 



which we infer frequencies from chances. This part of our 
inquiry will not be complete, therefore, until we have endeavoured 
to elucidate the conditions for the validity of an Inversion of 
Bernoulli's Theorem. 

3. The problem is usually discussed in terms of the happening 
of an event under certain conditions, that is to say, of the co- 
existence of the conditions, as affecting & particular event, with 
that event. The same problem can be dealt with more generally 
and more conveniently as an investigation of the correlation 
between two characters A(#) and B(#), which, as in Part III., 
are propositional functions which may be said to concur or co- 
exist when they are both true of the same argument x. Given 
that, within the field of our knowledge, B(#) is true for a certain 
proportion of the values of x for which A(a?) is true, what is the 
probability for a further value a of x that, if A(a) holds, B(a) will 
hold also ? 

Let us suppose that the occurrence of an instance of A(a?) is a 
sign of one of the events e x (#), e z (x) ... or e n (x), and that these 
are exhaustive, exclusive, and ultimate alternatives. By ex- 
haustive it is meant that, whenever there is an instance of A(cc), 
one of the e's is present ; by exclusive, that the presence of one 
of the e's is not a sign of the presence of any other, but not that 
the concurrence of two or more of the e's is in fact impossible ; 
by ultimate, that no one of the e's is a disjunction of two or more 
alternatives which might themselves be members of the e's. 
Let us assume that these alternatives are initially and ihroug'hout 
the argument equally probable, which, subject to the above con- 
ditions, is justified by the Principle of Indifference. We have no 
reason, that is to say, and no part of our evidence ever gives us 
one, for thinking that A(a) is more likely to be a sign of one of the 
e's than of any other, or even for thinking that some e's, although 
we do not know which, are more likely to occur than others. 
Let us also assume that, out of %(#), 62(0;) . . . e m (x), the set 
e 1 (cc), e z (x) . . . e z (#), and these only, are signs or occasions of 
B(#) ; and further that we have no evidence bearing on the actual 
magnitude of the integers I and w, so that the ratio l/m is the 
only factor of which the probability varies as the evidence 
accumulates. Let us assume, lastly, that our knowledge of the 
several instances of B(o;) is adequate to establish a perfect analogy 
between them ; the instances a, etc., of B(OJ), that is to say, must 

2 c 


not have anything in common ezcept B, unless we have reason 
to know that the additional resemblances are immaterial. Even 
by these considerable simplifications not every difficulty has 
been avoided. But a development along the usual lines with 
the assistance of Bernoulli's Theorem is now possible. 

Let l/m=q. If the value of q were known, the problem would 
be solved. For this numerical ratio would represent the prob- 
ability that A is, in any random instance, a sign of B ; and no 
further evidence, which satisfies the conditions of the preceding 
hypothesis, can possibly modify it. But in the inverse problem 
q is not known ; and our problem is to determine whether evidence 
can be forthcoming of such a kind, that, as this evidence is in- 
creased in quantity, the probability that A will be in any instance 
a sign of B, tends to a limit which lies between two determinate 
ratios, just as the probability of an inductive generalisation may 
tend towards certainty, when the evidence is increased in a 
manner satisfying given conditions. 

Let/(j) represent the proposition that q is the true value of 
l/m. Let q' represent the ratio of the number of instances actually 
before us in which A has been accompanied by B to that of the 
instances in which A has not been accompanied by B ; and let 
/'(?') l> e "khs proposition which asserts this. Now if the ratio q 
is known, then, subject to the assumptions already sbated, the 
number q must also represent the d priori probability in any 
instance, both before and after the results of other instances are 
known, that A, if it occurs, will be accompanied by B. We have, 
in fact, the conditions as set forth in Chapter XXIX., in which 
Bernoulli's Theorem can be validly applied, so that this theorem 
enables us to give a numerical value, for all numerical values of 
q and q', to the probability f(q')lh . /(?), which expression repre- 
sents the likelihood a priori of the frequency q' 9 given q. 

An application of the inverse formula allows us to infer from 
the above the d posteriori probability of j, given q', namely : 

/(/)/* ./(z) 

where the summation in the denominator covers all possible 
values of q. In rough applications of this inverse of Bernoulli's 
Theorem it has been usual to suppose that/(y)/A is constant for 
all values of j, that, in other words, all possible values of the 


ratio q are a priori equally likely. If this supposition were 
legitimate, the formula could be reduced to the algebraical ex- 

all the terms of which can be determined numerically by Ber- 
noulli's Theorem. It is easy to show that it is a maximum when 
q-q', i.e. that q' is the most probable value of l/m, and that, 
when the instances are very numerous, it is very improbable that 
l/m differs from q' widely. If, therefore, the number of instances 
is increased in such a manner that the ratio continues in the 
neighbourhood of q', the probability that the true value of Ifm 
is nearly q' tends to certainty; and, consequently, the prob- 
ability, that A is in any instance a sign of B, also tends to a 
magnitude which is measured by q'. 

I see, however, no justification for the assumption that all 
possible values of the ratio q are d priori equally likely. It is 
not even equivalent to the assumptions that all integral values 
of I and m respectively are equally probable. I am not satisfied 
either that different values of q, or that different values of m, 
satisfy the conditions which have been laid down in. Part I. for 
alternatives which are equal before the Principle of Indifference. 
There seem, for instance, to be relevant differences between the 
statement that A can arise in exactly two ways and the state- 
ment that it can arise in exactly a thousand ways. We must, 
therefore, be content with some lesser assumption and with a 
less precise form for our final conclusion. 

4 Since, in accordance with our hypothesis, m cannot exceed 
some finite number, and since I must necessarily be less than m, 
the possible values of m> and therefore of q, are finite in number. 
Perhaps we can assume, therefore, as one of our fundamental 
assumptions, that there is d priori a finite probability in favour 
of each of these possible values. Let p be the finite number 
which m cannot exceed. Then there is a finite probability for 
each of the intervals 1 

I* 2 2 * 3 /"- 1 4- i 

- to -, - to -, ... to 1 

IL /Ji IL /// /JL 

1 The intervals are supposed to include their lower but not their upper 


that q lies in this interval ; but we cannot assume that there is 
an equal probability for each interval. 
We must now return to the formula 

which represents the d posteriori probability of q, given q'. Since 
by sufficiently increasing the number of instances, the sum of 
terms /(20/(?) for possible values of q within a certain finite 
interval in the neighbourhood of q' can be made to exceed the 
other terms by any required amount, and since the sum of the 
values of /(<?)/& for possible values of q within this interval is 
finite, it clearly follows that a finite number of instances can 
make the probability, that q lies in an interval of magnitude 
l/p in the neighbourhood of q', to differ from certainty by less 
than any finite amount however small. 

5. We have, therefore, reached the main part of the conclusion 
after which we set out namely, that as the number of instances 
is increased the probability, that q is in the neighbourhood of 
^, tends towards certainty ; and hence that, subject to certain 
specified conditions, if the frequency with which B accompanies 
A is found to be q f in a great number of instances, then the 
probability that A will be accompanied by B in any further 
instance is also approximately q'. But we are left with the same 
vagueness, as in the case of generalisation, respecting the value 
of p, and the number of instances that we require. We know 
that we can get as near certainty as we choose by a finite number 
of instances, but what this number is we do not know. This is 
not very satisfactory, but it accords very well, I think, with 
what common sense tells us. It would be very surprising, in 
fact, if logic could tell us exactly how many instances we want, 
to yield us a given degree of certainty in empirical arguments. 

Nobody supposes that we can measure exactly the probability 
of an induction. Tet many persons seem to believe that in the 
weaker and much more difficult type of argument, where the 
association under examination has been in. our experience, not 
invariable, but merely in a certain proportion, we can attribute 
a definite measure to our future expectations and can claim 
practical certainty for the results of predictions which lie within 
relatively narrow limits. Coolly considered, this is a preposter- 


ous claim, which would have been universally rejected long ago, 
if those who made it had not so successfully concealed them- 
selves from the eyes of common sense in a maze of mathematics. 
6. Meantime we are in danger of forgetting that, in order to 
reach even our modified conclusion, material assumptions have 
been introduced. In the first place, we are faced with exactly 
the same difficulties as in the case of universal induction dealt 
with in Part III., and our original starting-point must be the 
same. We have the same difficulty as to how our initial prob- 
ability is to be obtained ; and I have no better suggestion to offer 
in this than in the former case namely, the supposed principle 
of a limitation of independent variety in experience. We have 
to suppose that if A and B occur together (i.e. are true of the 
same object), this is some just appreciable reason for supposing 
that in this instance they have a common cause ; and that, if 
A occurs again, this is a just appreciable reason for supposing 
that it is due to the same cause as on the former occasion. But 
in addition to the usual inductive hypothesis, the argument has 
rested on two particularly important assumptions, first, that we 
have no reason for supposing that some of the events of which 
A may be a sign are more likely to be exemplified in some of the 
particular instances than in others, and secondly, that the analogy 
amongst the examined B's is perfect. The first assumption 
amounts, in the language of statisticians, to an assumption of 
random sampling from amongst the A's. The second assumption 
corresponds precisely to the similar condition which we discussed 
fully in connection with inductive generalisation. The instances 
of A(x) may be the result of random sampling, and yet it may 
still be the case that there are material circumstances, common . 
to all the examined instances of B(#), yet not covered by the 
statement A(ce)B(#). In so far as these two assumptions are not 
justified, an element of doubt and vagueness, which is not easily 
measured, assails the argument. It is an element of doubt 
precisely similar to that which exists in the case of generalisa- 
tion. But we are most likely to forget it. For having overcome 
the difficulties peculiar to correlation, 1 it is, possibly, not un- 

1 I am here using this term in distinction to generalisation ; that is to say, 
I call the statement that A(x) is always accompanied by ~B(x) a generalisation, 
and the statement that A(a;) is accompanied by B(a?) in a certain proportion 
of cases a correlation. This is not quite identical with its use by modern 


natural for a statistician to feel as if he had overcome all the 

In practice, however, our knowledge, in cases of correlation 
just as in cases of generalisation, will seldom justify the assump- 
tion of perfect analogy between the B's ; and we shall be faced 
by precisely the same problems of analysing and improving our 
knowledge of the instances, as in the general case of induction 
already examined. If B has invariably accompanied A in 100 
cases, we have all kinds of difficulties about the exact character 
of our evidence before we can found on this experience a valid 
generalisation. If B has accompanied A, not invariably, but 
only 50 times in the 100 cases, clearly we have just the same 
kind of difficulties to face, and more too, before we can announce 
a valid correlation. Out of the mere analysed statement that B 
has accompanied A as often as not in 100 cases, without precise 
particulars of the cases, or even if there were 1,000,000 cases 
instead of 100, we can conclude very little indeed. 



1. No one supposes that a good induction can be arrived at 
merely by counting cases. The business of strengthening the 
argument chiefly consists in determining whether the alleged 
association is stable, when the accompanying conditions are 
varied. This process of improving the Analogy, as I have called 
it in Part III., is, both logically and practically, of the essence of 
the argument. 

Now in statistical reasoning (or inductive correlation) that 
part of the argument, which corresponds to counting the cases 
in inductive generalisation, may present considerable technical 
difficulty. This is especially so in the particularly complex cases 
of what in the next chapter ( 9) I shall term Quantitative Cor- 
relation, which have greatly occupied the attention of English 
statisticians in recent years. But clearly it would be an error to 
suppose that, when we have successfully overcome the mathe- 
matical or other technical difficulties, we have made any greater 
progress towards establishing our conclusion than when, in the 
case of inductive generalisation, we have counted the cases but 
have not yet analysed or compared the descriptive a:nd non- 
numerical differences and resemblances. In order to get a good 
scientific argument we still have to pursue precisely the same 
scientific methods of experiment, analysis, comparison, and 
differentiation as are recognised to be necessary to establish any 
scientific generalisation. These methods are not reducible to a 
precise mathematical form for the reasons examined in Part III. 
of this treatise. But that is no reason for ignoring them, .or for 
pretending that the calculation of a probability, which takes into 



account nothing whatever except the numbers of the instances, 
is a rational proceeding. The passage already quoted from 
Leibniz (In eocemplis juridicis politicisque plerumque non tamen 
subtili cakulo opus est, quam accurata omnium drcumstantiarum 
enumerations) is as applicable to scientific as to political inquiries. 
Generally speaking, therefore, I think that the business of 
statistical technique ought to be regarded as strictly limited to 
preparing the numerical aspects of our material in an intelligible 
form, so as to be ready for 'the application of the usual inductive 
methods. Statistical technique tells us how to ' count the cases ' 
when we are presented with complex material. It must not 
proceed also, except in the exceptional case where our evidence 
furnishes us from the outset with data of a particular kind, to 
turn its results into probabilities ; not, at any rate, if we mean 
by probability a measure of rational belief. 

2. There is, however, one type of technical, statistical investi- 
gation not yet discussed, which seems to me to be a valuable 
aid to inductive correlation. This method consists in breaking 
up a statistical series, according to appropriate principles, into 
a number of sub-series, with a view to analysing and measuring, 
not merely the frequency of a given character over the aggregate 
series, but the stability of this frequency amongst the sub- 
series ; that is to say, the series as a whole is divided up by some 
principle of classification into a set of sub-series, and the fluctua- 
tion of the statistical frequency under examination between the 
various sub-series is then examined. It is, in fact, a technical 
method of increasing the Analogy between the instances, in the 
sense given to this process in Part III. 

3. The method of analysing statistical series, as opposed to 
the Laplacian or mathematical method, one might designate the 
inductive method. Independently of the investigations of 
Bernoulli or Laplace, practical statisticians began at least as early 
as the end of the seventeenth century 1 to pay attention to the 
stability of statistical series when analysed in this manner. 
Throughout the eighteenth century, students of mortality 
statistics, and of the ratio of male to female births (including 
Laplace himself), paid attention to the degree of constancy of the 

1 Graunt in Ms Natural and Political Observations upon the Bills of Mortality 
has been quoted as one of the earliest statisticians to pay attention to these 


ratios over different parts of their series of instances as well as 
to their average value over the whole series. And in the early 
part of the nineteenth century, Quetelet, as we have already 
noticed, widely popularised the notion of the stability of various 
social statistics from year to year. Quetelet, however, sometimes 
asserted the existence of stability on insufficient evidence, and 
involved himself in theoretical errors through imitating the 
methods of Laplace too closely ; and it was not until the last 
quarter of the nineteenth century that a school of statistical 
theory was founded, which gave to this way of approaching the 
problem the system and technique which it had hitherto lacked, 
and at the same time made explicit the contrast between this 
analytical or inductive method and the prevailing mathematical 
theory. The sole founder of this school was the German econo- 
mist, Wilhelm Lexis, whose theories were expounded in a series 
of articles and monographs published between the years 1875 
and 1879. For some years Lexis's fundamental ideas did not 
attract much notice, and he himself seems to have turned his 
attention in other directions. But more recently a considerable 
literature has grown up round them in Germany, and their full 
purport has been expressed with more clearness than by Lexis 
himself although no one, with the exception of Ladislaus von 
Bortkiewicz, has been able to make additions to them of any 
great significance. 1 Lexis devised his theory with an immediate 
view to its practical application to the problems of sex ratio and 
mortality. The fact that his general theory is so closely inter- 
mingled with these particular applications of it is, probably, a 
part explanation of the long interval which elapsed before the 
general theoretical importance of his ideas was widely realised. 
I cannot help doubting how fully Lexis himself realised it in the 
first instance. It would certainly be easy to read his earlier 
contributions to the question without appreciating their general- 
ised significance. After 1879 Lexis added nothing substantial to 
his earlier work, and later developments are mainly due to Von 

1 A list of Lexis's principal writings on these topics will be found in the 
Bibliography. There is little of first-rate importance which is not contained 
either in the volume, Zur Theorie der Massenerscheinungen in der menschlichen 
QeselUchaft f or in the AbTwndlungen zur Theorie der Bevdlkerungs- und Moral- 
Statistic. In this latter volume the two important articles on *' Die Theorie der 
Stabilitat statistischer Reihen" and on "Das Geschlechtsverhaltnis der 
Geborenen und die Wahrscheinlichkeitsrechnung," originally published in Con- 
rad's Jahrb'iiche, are reprinted. 


Bortkiewicz. Those of the latter's writings, which have an 
important bearing on the relation between probability and 
statistics, are given in the Bibliography. 1 

On the logic and philosophy of Probability writers of the 
school of Lexis are in general agreement with Von Kries ; but this 
seems to be due rather to the reaction which is common both to 
him and to them against the Laplacian tradition, than to any 
very intimate theoretical connection between Von Kries's main 
contributions to Probability and those of Lexis, though it is true 
that both show a tendency to find the ultimate basis of Probability 
in physical rather than in logical considerations. I am not 
acquainted with much work, which has been appreciably influ- 
enced by Lexis, written in other languages than German (including 
with Germans, that is to say, those Russians, Austrians, and Dutch 
who usually write in German, and are in habitual connection with 
the German scientific world). In France Dormoy 2 published 
independently and at about the same time as Lexis some not 
dissimilar theories, but subsequent French writers have paid 
little attention to the work of either. Such typical French 
treatises as that of Bertrand, or, more recently, that of Borel, 
contain no reference to them. 3 In Italy there has been some 
discussion recently on the work of Von Bortkiewicz. Among 
Englishmen Professor Edgeworth has shown a close acquaintance 
with the work of the German school, 4 he providing for nearly forty 
years past, on this as on other matters where the realms of 

1 The reader may be specially referred to the Kritische Betrachtungen zur 
theoretischen Statistik (first instalment the later instalments being of less interest 
to the student of Probability), the Anwendungen der WahrscheMichkeitsrechnung 
auf Statistik, and Homogeneitdt und Stabilitdt in der Statistik. Of other German 
and Russian -writers it will be sufficient to mention here Tschuprow, who in 
" Die Aufgaben der Theorie der Statistik " (Schinoller's Jahrbuch, 1905) and " Zur 
Theorieder Stabilitat statistischer Reihen " (Skandinavisk Aktuarietidstoift) gives 
by far the best and most lucid general accounts that are available of the doctrines 
of the school, he alone amongst these authors writing in a style from which 
the foreign reader can derive pleasure, and Czuber, who in his Wahrschein- 
lichkeitsrechnung (vol. iL part iv. section 1) supplies a useful mathematical 

2 Journal des actuairesfranQais, 1874, and Theorie mathematique des assurances 
sur la vie, 1878 ; on the question of priority see Lexis, AbTiandlungen, p. 130. 

s Though both these writers touch on closely cognate matters, where Lexis's 
investigations would be highly relevant Bertrand, Cakul, pp. 312-314 ; Borel, 
EUments, p. 160. 

4 See especially his "Methods of Statistics " in the Jubilee Volume of the 
Stat. Journ., 1885, and "Application of the Calculus of Probabilities to 
Statistics," International Statistical Institute Bulletin, 1910. 


Statistics and Probability overlap, almost the only connecting 
link between English and continental thought. 

Nevertheless, an account in English of the main doctrines of 
this school is still lacking. It would be outside the plan of the 
present treatise to attempt such an account here. But it may 
be useful to give a short summary of Lexis's fundamental ideas. 
After giving this account I shall find it convenient, in proceeding 
to my own incomplete observations on the matter, to approach 
it from a rather different standpoint from that of Lexis or of 
Von Bortkiewicz, though not for that reason the less influenced 
or illuminated by their eminent contributions to this problem. 

4. It will be clearer to begin with some analysis due to Von 
Bortkiewicz, 1 and then to proceed to the method of Lexis him- 
self, although the latter came first in point of time. 

A group of observations may be made up of a number of sub- 
groups, to which different frequencies for the character under 
investigation are properly applicable. That is to say, a propor- 

tion of the observations may belong to a group, for which, given 
the frequency, the a priori probability of the character under 
observation in a particular instance would be p v a proportion -- 

may belong to a second group for which p% is the probability, and 
so on. In this case, given the frequencies for the sub-groups, 
the probability p for the group as a whole would be made up as 
follows : 

We may call p a general probability, and p, etc., special prob- 
abilities. But the special probabilities may in their turn be 
general probabilities, so that there may be more than one way 
of resolving a general probability into special probabilities. 

If PI =PZ = . . . . =p, then p 9 for that particular way of resolv- 
ing tfre total group into partial groups, is, in Bortkiewicz's termin- 
ology, indifferent. lip is indifferent for all conceivable resolutions 
into partial groups, 2 then, borrowing a phrase from Von Kries, 
Bortkiewicz says of it that it has a definitive interpretation. In 

1 What follows is a free rendering of some passages in his Kritiscfe 

2 This is clearly a very, loose statement of what BortMewicz really means. 


dealing with d priori probabilities, we can resolve a total prob- 
ability until we reach the special probabilities of each individual 
case ; and if we find that all these special probabilities are equal, 
then, clearly, the general probability satisfies the condition for 
definitive interpretation. 

So far we have been dealing with d priori probabilities. But 
the object of the analysis has been to throw light on the inverse 
problem. We want to discover in what conditions we can regard 
an observed frequency as being an adequate approximation to a 
definitive general probability. 

If p f is the empirical value of p (or, as I should prefer to call 
it, the frequency) given by a series of n observations, we may 

Even if this particular way of resolving the series of observations 
is indifferent, the actually observed frequencies p^ 9 p 2 ', etc., may 
nevertheless be unequal, since they may fluctuate round the 
norm p' through the operation of ' chance ' influences. If, 
however, n v n 2 , etc., are large, we can apply the usual Bernoullian 
formula to discover whether, if there was a norm p', the diverg- 
ences of pi, p 2 ' 3 etc., from it are within the limits reasonably attri- 
butable on Bernoullian hypotheses to e chance ' influences. We 
can, however, only base a sound argument in favour of the 
existence of a ' definitive ' probability p' by resolving our 
aggregate of instances into sub-series in a great variety of ways, 
and applying the above calculations each time. Even so, some 
measure of doubt must remain, just as in the case of other 
inductive arguments. 

Bortkiewicz goes on to say that probabilities having definitive 
interpretation (definitive Bedeutung) may be designated ele- 
mentary probabilities (ElernmtarwahrscheinUchkeiten). But the 
probabilities which usually arise in statistical inquiries are not 
of this type, and may be termed average probabilities (Durch- 
schnittswaJirscheinlichkeiten). That is to say, a series of observed 
frequencies (or, as he calls them, empirical probabilities) does not, 
as a rule, group itself as it would if the series was in fact subject 
to an elementary probability. 

5. This exposition is based on a philosophy of Probability 
different from mine; but the underlying .ideas are capable of 


translation. Suppose that one is endeavouring to establish an 
inductive correlation, e.g. that the chance of a male birth is m. 
The conclusion, which we are seeking to establish, takes no 
account of the place or date of birth or the race of the parents, 
and assumes that these influences are irrelevant. Now, if we had 
statistics of birth ratios for all parts of the world throughout the 
nineteenth century, and added them all up and found that the 
average frequency of male births was m, we should not be justified 
in arguing from this that the frequency of male births in England 
next year is very unlikely to diverge widely from m. For this 
would involve the unwarranted assumption, in Bortkiewicz's 
terminology, that the empirical probability m is elementary for 
any resolution dependent on time or place, and is not an average 
probability compounded out of a series of groups, relating to 
different times or places, to each of which a distinct special 
probability is applicable. And, in my terminology, it would 
assume that variations of time and place were irrelevant to the 
correlation, without any attempt having been made to employ 
the methods of positive and negative Analogy to establish this. 

We must, therefore, break up our statistical material into 
groups by date, place, and any other characteristic which our 
generalisation proposes to treat as irrelevant. By this means 
we shall obtain a number of frequencies ?%', w 2 ', m 3 ', .... m/', 
w 2 ", w 3 ", .... etc., which are distributed round the average 
frequency m. For simplicity let us consider the series of fre- 
quencies m/, w 2 ', m 3 ', .... obtained by breaking up our 
material according to the date of the birth. If the observed 
divergences of these frequencies from their mean are not signifi- 
cant, we have the beginnings of an inductive argument for 
regarding date as being in this connection irrelevant. 

6. At this point Lexis's fundamental contribution to the 
problem must be introduced. He concentrated his attention on 
the nature of the dispersion of the frequencies %', m 2 ', m z ' . . . . 
round their mean value m ; and he sought to devise a technical ' 
method for measuring the degree of stability displayed by the , 
series of sub-frequencies, which are yielded by the various possible 
criteria for resolving the aggregate statistical material into a 
number of constituent groups. 

For this purpose he classified the various types of dispersion 
which could occur. It may be the case that some of the sub- 


frequencies show such wide and discordant variations from the 
mean as to suggest that some significant Analogy has been over- 
looked. In this event the lack of symmetry, which characterises 
the oscillations, may be taken to indicate that some of the sub- 
groups are subject to a relevant influence, of which we must take 
account in our generalisation, to which some of the other sub- 
groups are not subject. 

But amongst the various types of dispersion Lexis found one 
class clearly distinguishable from all the others, the peculiarity 
of which is that the individual values fluctuate in a ' purely 
chance ' manner about a constant fundamental value. This 
type he called typical (typiscJie) dispersion. He meant by this 
that the dispersion conformed approximately to the distribution 
. larhich would be given by some normal law of error. 

The nest stage of Lexis's argument 1 was to point out that 
series of frequencies which are typical in character may have as 
their foundation either a constant probability, 2 or one which is 
itself subject to chance variations about a mean. The first case 
is typified by the example of a series of sets of drawings of balls, 
each set being drawn from a similar urn ; the second case by the 
example of a series of sets of drawings, the urns from which each 
set is drawn being not similar, but with constitutions which vary 
in a chance manner about a mean. 

As his measure of dispersion Lexis introduces a formula, which 
is evidently in part conventional (as is the case with so many 
other statistical formulae, the particular shape of which is often 
determined by mathematical convenience rather than by any 
more fundamental criterion). He expresses himself as follows. 
Where the underlying probability is constant, the probable error 

,. , , .... - 

in a particular frequency a pnon is r=*p /-- - where 

V 9 

p = 4769, v is the underlying probability, and g is the number of 
instances to which the frequency refers. This follows from the 
usual Bernoullian assumptions. Now let R be the corresponding 
expression derived d posteriori by reference to the actual devia- 
tions of a series of observed frequencies from their mean, so that 

1 I am here f ollowing fairly closely his paper, Uber die Theorie der Stabilitat 
statisticlier Keihen," reprinted in his Abhandlungen zur Theorie der Bevdlkerunas- 
und MordLStatiatik, pp. 170-212. 

2 This mode of expression, which is not in accurate conformity with my 
philosophy of Probability, is Lexis's, not mine. His meaning is intelligible. 



n / - - 

where [S 2 ] is tlie sum of the squares of the devia- 

tions of the individual frequencies from their mean and n is their 
number. Now, if the observed facts are due to merely chance 
variations about a constant v s we must have approximately 
R=r, though, if g is small, comparatively wide deviations be- 
tween R and r will not be significant. If, on the other hand, v 
itself is not constant but is subject to chance variations, the case 
stands differently. For the fluctuations of the observed fre- 
quencies are now due to two components. The one which would 
be present, even if the underlying probability were constant, 
Lexis terms the ordinary or unessential component ; the other 
he terms the physical component. If p is the probable deviation 
of the various values of v from their mean, then, on the same 
assumptions and as a deduction from the same theory as before, 
R will tend to equal not r but ^/r 2 +p z . In this event R cannot 
be less than r. If, therefore, R<r, one must suppose that the 
individual instances of each several series on which each frequency 
is based are not independent of one another. Such a series 
Lexis terms an organic or dependent (gebundene) series, and 
explains that it cannot be handled by purely statistical methods. 
Since, therefore, we have three types of series, differing 
fundamentally from one another according as R=r, >r, or <r, 


Lexis puts = Q, and takes Q as his measure of dispersion. 1 If 

Q = 1, we have normal dispersion ; if Q > 1, we have supernormal 
dispersion; and if Q<1, we have subnormal dispersion, which is 
an indication that the series is e organic.' 

If the number of instances on which the frequencies are based 
is very great, r becomes negligible in comparison with p (the 
physical component), and, therefore, R = +/r 2 +p* becomes 
approximately R =y. On the other hand, if p is not very large 
and the base number of instances is small, p becomes negligible 

1 la Tschuprow's notation (Die Aufgaben d&r Theorie der Statistik, p. 45), 


Q=P/C, where P (the Physical moduli**) -A/ *= x - and C (the Com- 


binatorial modulus) =x/ g M being the number of instances in each 

set, n the number of sets ? p% the frequency for set k, and p the mean of the 
n frequencies, 


in comparison with r, and we have a delusive appearance of 
normal dispersion. 1 Lexis well illustrates the former point by 
the example that the statistics of the ratio of male to female 
births for the forty-five registration districts of England over the 
years 1859-1871 approximately satisfy the relation K=r. But 
if we take the figures for all England over those thirteen years, 
although the extreme limits of the fluctuation of the ratio about 
its mean 1 -042 are 1 -035 and 1 -047, nevertheless R = 2-6 and r = 1-6, 
so that Q= 1-625 ; the explanation being that the base number 
of instances, namely 730,000, is so large that r is very small, with 
the result that it is swamped by the physical component p. And 
he illustrates the latter point by the assertion that, if in 20 or 30 
series each of 100 draws from an urn containing black and white 
balls equally, the number of black balls drawn each time were 
only to vary between 49 and 51, he would have confidence that 
the game was in some way falsified and that the draws were not 
independent. That is to say, undue regularity is as fatal to the 
assumption of Bernoullian conditions as is undue dispersion. 

7. In a characteristic passage 2 Professor Edgeworth has applied 
these theories to the frequency of dactyls in successive extracts 
from the Aeneid. The mean for the line is 1-6, exclusive of the 
fifth foot, thus sharply distinguishing the Virgilian line from the 
Ovidian, for which the corresponding figure is 2-2. But there is 
also a marked stability. " That the Mean of any five lines 
shoulcl differ from the general Mean by a whole dactyl is proved 
to be an exceptional phenomenon, about as rare as an Englishman 
measuring 5 feet, or 6 feet 3 inches. An excess of two dactyls 
in the Mean of five lines would be as exceptional as an Englishman 
measuring 6 feet 10 inches." But not only so the stability is 
excessive, and the fluctuation is less " than that which is obtained 
upon the* hypothesis of pure sortition. If we could imagine 
dactyls and spondees to be mixed up in the poet's brain in the 
proportion of 16 to 24 and shaken out at rand,om, the modulus 
in the number of dactyls would be 1-38, whereas we have con- 
stantly obtained a smaller number, on an average (the square 
root of the average fluctuation) 1-2." On Lexian principles 
these statistical results would support the hypothesis that the 

1 This is part of the explanation of BortMewioz's Law of Small Numbers. 
See also p. 401. 

* " On Methods of Statistics," Jubilee Volume of the Royal Statistical Society, 
P. 2J1. 


series under investigation is ' organic ' and not subject to 
Bernoullian conditions, an hypothesis in accordance with our 
ideas of poetry. That Edgeworth should have put forward 
this example in criticism of Lexis's conclusions, and that Lexis x 
should have retorted that the explanation was to be found in 
Edgeworth's series' not consisting of an adequate number of 
separate observations, indicates, if I do not misapprehend them, 
that these authorities are at fault in the principles, if not of 
Probability, of Poetry. 

The dactyls of the Virgilian hexameter are, in fact, a very 
good example of what has been termed connexite, leading to sub- 
normal dispersion. The quantities of the successive feet are not 
independent, and the appearance of a dactyl in one foot diminishes 
the probability of another dactyl in that line. It is like the case 
of drawing black and white balls out of an urn, where the balls 
are not replaced. But Lexis is wrong if he supposes that a super- 
normal dispersion cannot also arise out of connexite> or organic 
connection between the successive terms. It might have been 
the case that the appearance of a dactyl in one foot increased 
the probability of another dactyl in that line. He should, I 
think, have contemplated the result R>r as possibly indicating 
a non-typical, organic series, and should not have assumed that, 
where E is greater than r, it is of the form \/r* 

In short, Lexis has not pushed his analysis far enough, and he 
has not fully comprehended the character of the underlying 
conditions. But this does not affect the fact that it was he who 
made the vital advance of taking as the unit, not the single 
observation, but the frequency in given conditions, and of con- 
ceiving the nature of statistical induction as consisting in the 
examination, and if possible the measurement, of the stability 
of the frequency when the conditions are varied. 

8. There is one special piece of work illustrative of the above 
methods, due to Von Bortkiewicz, which must not be overlooked, 
and which it is convenient to introduce in this place the so- 
called Law of Small Numbers. 2 

Quetelet, as we have seen in Chapter XXVIII., called attention 

1 " Uber die WakrscheinHchkeitsrechnung," p. 444 (see Bibliography). 

2 There are numerous references to this phenomenon in periodical literature ; 
but it is sufficient to refer the reader to Von Bortkiemcz's Das Q&etz der kleinen 




PT. V 

to the remarkable regularity of comparatively rare events. Von 
BortMewicz has enlarged Quetelet's catalogue with modern 
instances out of the statistical records of bureaucratic Germany. 
The classic instance, perhaps, is the number of Prussian cavalry- 
men killed each year by the kick of a horse. The table is worth 
giving as a statistical curiosity. (The period is from 1875 to 
1894 ; G stands for the Corps of Guards, and I.-XV. for the 
15 Army Corps.) 





















































































































































The agreement of this table with the theoretical results of a 
random distribution of the total number of casualties is remark- 
ably close : x 

Casualties in a 

Humber of Occasions on which the Annual 
Casualties in a Corps reach the Figure 
in Column 1. 

















5 and more 


Other instances are furnished by the numbers of child suicides 
in Pmssiaj and the like. 

It is Von Bortkiewicz's thesis that these observed regularities 

1 BortMe'wicz, op. cit. p. 24. 


Lave a good theoretical explanation behind them, which. he 
dignifies with, the name of the Law of Small Numbers. 

The reader will recall that, according to the theory of Lexis, 
his measure of stability Q is, in the more general case, made up 
of two components r and p, combined in the expression \/r* +p 2 , 
of which one is due to fluctuations from the average of the con- 
ditions governing all the members of a series, which furnishes us 
with one of our observed frequencies, and of which the other is 
due to fluctuations in the individual members of the series about 
the true norm of the series. Bortkiewicz carries the same 
analysis a little further, and shows that Lexis's Q is of the form 
+/l+(n-l)c 2 , where n is the number of times that the event 
occurs in each series. 1 That is to say, Q increases with n, and, 
when n is small, Q is likely to exceed unity to a less extent than 
when n is large. To postulate that n is small, is, when we are 
dealing with observations drawn from a wide field, the same 
thing as to say that the event we are looking for is a comparatively 
rare one. This, in brief, is the mathematical basis of the Law 
of Small Numbers. 

In his latest published work on these topics, 2 Von Bortkiewicz 
builds his mathematical structure considerably higher, without, 
however, any further underpinning of the logical foundations 
of it. He has there worked out further statistical constants, 
arising out of the conceptions on which Lexis's Q is based (the 
precise bearing of which is not made any clearer by his calling 
them coefficients of syndromy), which are explicitly dependent 
on the value of n ; and he elaborately compares the theoretical 
value of the coefficients with the observed value in certain actual 
statistical material. He concludes with the thesis, that Homo- 
geneity and Stability (defined as he defines them) are opposed 
conceptions, and that it is not correct to premise, that the larger 
statistical mass is as a rule more stable than the smaller, unless 

1 I refer the reader to the original, op. cit. pp. 29-31, for the interpretation 
of c (which is a function of the mean square errors arising in the course of the 
investigation) and for the mathematical argument by which the above result 
is justified. 

2 " Homogeneitat und Stabilitat in der Statistik," published in the Skandi- 
navisk Aktuarietidskrift, 191 8. Those readers, who look up my references, 
will, I think, agree with me that Von Bortkiewicz does not get any less 
obscure as he goes on. The mathematical argument is right enough, and 
often brilliant. But what it is all really about, what it all really amounts to, 
and what the premisses are, it becomes increasingly perplexing to decide. 


we also assume that the larger mass is less homogeneous. At this 
point, it would have helped, if Von Bortkiewicz, excluding from 
his vocabulary homogeneity, paradromy, ry' M , and the like, had 
stopped to tell in plain language where his mathematics had led 
him, and also whence they had started. But like many other 
students of Probability he is eccentric, preferring algebra to earth. 

9. Where, then, though an admirer, do I criticise all this ? I 
think that the argument has proceeded so far from the premisses, 
that it has lost sight of them. If the limitations prescribed by 
the premisses are kept in mind, I do not contest the mathematical 
accuracy of the results. But many technical terms have been 
introduced, the precise signification and true limitations of which 
will be misunderstood if the conclusion of the argument is allowed 
to detach itself from the premisses and to stand by itself. I will 
illustrate what I mean by two examples from the work of Von 
Bortkiewicz described above. 

Von Bortkiewicz enunciates the seeming paradox that the 
larger statistical mass is only, as a rule, more stable if it is less 
homogeneous. But an illustration which he himself gives shows 
how misleading his aphorism is. The opposition between 
stability and homogeneity is borne out, he says, by the judgment 
of practical men. For actuaries have always maintained, that 
their results average out better, if their cases are drawn from a 
wide field subject to variable conditions of risk, whilst they are 
chary of accepting too much insurance drawn from a single 
homogeneous area which means a concentration of risk. But 
this is really an instance of Von Bortkiewicz's own distinction 
between a general probability p and special probabilities p l etc., 

If we are basing* our calculations on p and do not know p l9 p^ 
etc., then these calculations are more likely to be borne out by 
the result if the instances are selected by a method which spreads 
them over all the groups 1, 2, etc., than if they are selected by a 
method which concentrates them on group 1. In other words, 
the actuary does not like an undue proportion of his cases to be 
drawn from a group which may be subject to a common relevant 
influence for which he has not allowed. If the d priori calculations 
are based on the average over a field which is not homogeneous 


in all its parts, greater stability of result will be obtained if the 
instances are drawn from all parts of the non-homogeneous 
total field, than if they are drawn now from one homogeneous 
sub-field and now from another. This is not at all paradoxical. 
Yet I believe, though with hesitation, that this is all that Von 
Bortkiewicz's elaborately supported mathematical conclusion 
really amounts to. 

My second example is that of the Law of Small Numbers. 
Here also we are presented with an apparent paradox in the 
statement that the regularity of occurrence of rare events is more 
stable than that of commoner events. Here, I suspect, the 
paradoxical result is really latent in the particular measure of 
stability which has been selected. If we look back at the figures, 
which I have quoted above, of Prussian cavalrymen killed by 
the kick of a horse, it is evident that a measure of stability could 
be chosen according to which exceptional instability would be 
displayed by this particular material ; for the frequency varies 
from to 4 round a mean somewhat less than unity, which is a 
very great percentage fluctuation. In fact, the particular measure 
of stability which Von BortMewicz has adopted from Lexis has 
about it, however useful and convenient it may be, especially for 
mathematical manipulation, a great deal that is arbitrary and 
conventional. It is only one out of a great many possible 
formulae which might be employed for the numerical measure- 
ment of the conception of stability, which, quantitatively at 
least, is not a perfectly precise one. The so-called Law of Small 
Numbers is, therefore, little more than a demonstration that, 
where rare events are concerned, the Lexian measure of stability 
does not lead to satisfactory results. Like some other formulae 
which involve a use of Bernoullian methods in an approximative 
form, it does not lead to reliable results in all circumstances. 
I should add that there is one other element which may contribute 
to the total psychological reaction of the reader's mind to the 
Law of Small Numbers, namely, the surprising and piquant 
examples which are cited in support of it. It is startling and 
even amusing to be told that horses kick cavalrymen with the 
same sort of regularity as characterises the rainfall. But oux 
surprise at this particular example's fulfilling the Law of Great 
Numbers has little or nothing to do with the exceptional stability 
about which, the Law of Small Numbers purports to concern itself. 



1. THERE is a great difference between the proposition " It is 
probable that every instance of this generalisation is true " and 
the proposition " It is probable of any instance of this generalisa- 
tion taken at random that it is true." The latter proposition 
may remain valid, even if it is certain that some instances of the 
generalisation are false. It is more likely than not, for example, 
that any number will be divisible either by two or by three, but 
it is not more likely than not that all numbers are divisible either 
by two or by three. 

The first type of proposition has been discussed in Part III. 
under the name of Universal Induction. The latter belongs to 
Inductive Correlation or Statistical Induction, an attempt at the 
logical analysis of which must be my final task. 

2. 'What advocates of the Frequency Theory of Probability 
wrongly believe to be characteristic of all probabilities, namely, 
that they are essentially concerned not with, single instances but 
with series of instances, is, I think, a true characteristic of 
statistical induction. A statistical induction either asserts the 
probability of an instance selected at random from a series of 
propositions, or else it assigns the probability of the assertion, 
that the truth frequency of a series of propositions (i.e. the 
proportion of true propositions in the series) is in the neighbour- 
hood of a given value. In either case it is asserting a char- 
acteristic of a series of propositions, rather than of a particular 

Whilst, theref ore, our unit in the case of Universal Induction 
is a .single instance which satisfies both the condition and the 
conclusion of our generalisation, our unit in the case of&J"atistical 


Induction is not a single instance, but a set or series of instances, 
all of which satisfy the condition of our generalisation but 
which satisfy the conclusion only in a certain proportion of cases. 
And whilst in Universal Induction we build up our argument by 
examining the known positive and negative Analogy shown in a 
series of single instances, the corresponding task in Statistical 
Induction consists in examining the Analogy shown in a series of 
series of instances. 

3. We are presented, in problems of Statistical Induction, with 
a set of instances all of which satisfy the conditions of our general- 
isation, and a proportion / of which satisfy its conclusion ; and 
we seek to generalise as to the probable proportion in which 
further instances will satisfy the conclusion. 

Now it is useless merely to pay attention to the proportion (or 
frequency) / discovered in the aggregate of the instances. For 
any collection whatever, comprising a definite number of objects, 
must, if the objects be classified with reference to the presence 
or absence of any specified characteristic whatever, show some 
definite proportion or statistical frequency of occurrence ; so that 
a mere knowledge of what this frequency is can have no appreci- 
able bearing on what the corresponding frequency will be for 
some other collection of objects, or on the probability of finding 
the characteristic in an object which does not belong to the 
original collection. We should be arguing in the same sort of 
way as if we were to base a universal induction as to the 
concurrence of two characteristics on a single observation of this 
concurrence, and without any analysis of the accompanying 

Let the reader be clear about this. To argue from the mere 
fact that a given event has occurred invariably in a thousand 
instances under observation, without any analysis of the circum- 
stances accompanying the individual instances, that it is likely 
to occur invariably in future instances, is a feeble inductive 
argument, because it takes no account of the Analogy. Neverthe- 
less an argument of this Mnd is not entirely worthless, as we have 
seen in Part III. But to argue, without analysis of the instances, 
from the mere fact that a given event has a frequency of 10 per 
cent in the thousand instances under observation, or even in a 
million instances, that its probability is 1/10 for the next instance, 
or that it is likely to have a frequency near to 1/10 in a further 


set of observations, is a far feebler argument ; indeed it is hardly 
an argument at all. Yet a good deal of statistical argument is not 
free from this reproach ; though persons of common sense often 
conclude better than they argue, that is to say, they select for 
credence, from amongst arguments similar in form, those in 
favour of which there is in fact other evidence tacitly known to 
them though not explicit in the premisses as stated. 

4. The analysis of statistical induction is not fundamentally 
different from that of universal induction already attempted in 
Part III. But it is much more intricate ; and I have experienced 
exceptional difficulty, as the reader may discover for himself in 
the following pages, both in clearing up my own mind about it 
and in expounding my conclusions precisely and intelligibly. I 
propose to begin with a few examples of what commonly impresses 
us as good arguments in this field, and also of the attendant 
circumstances which, if they were known to exist, might be held 
to justify such a mode of reasoning ; and, having thus attempted 
to bring before the reader's mind the character of the subject- 
matter, to proceed to an abstract analysis. 

Example One. Let us investigate the generalisation that the 
proportion of male to female births is m. The fact that the 
aggregate statistics for England during the nineteenth century 
yield the proportion m would go no way at all towards justifying 
the statement that the proportion of male births in Cambridge 
next year is likely to approximate to m. Our argument would 
be no better if our statistics, instead of relating to England during 
the nineteenth century, covered all the descendants of Adam. 
Bat if we were able to break up our aggregate series of instances 
into a series of sub-series, classified according to a great variety 
of principles, as for example by date, by season, by locality, by 
the class of the parents, by the sex of previous children, and so 
forth, and if the proportion of male births throughout these sub- 
series showed a significant stability in the neighbourhood of m, 
then indeed we have an argument worth something. Otherwise 
we must either abandon our generalisation, amplify its conditions, 
or modify its conclusion. 

Example Two. Let us take a series of objects $ all alike in 
some specified respect, this resemblance constituting membership, 
of the class 3? ; let us determine of how many members of the 
series a certain property < is true, the frequency of which is to be 


the subject of our generalisation ; and if a proportion / of the 
series s have the property <, we may say that the series 5 has a 
frequency /for the property <. 

Now if the whole field F has a finite number of constituents, 
it must have some determinate frequency p, and if, therefore, 
we increase the comprehensiveness of s until eventually it 
includes the whole field, / must come in the end to be equal 
to p. This is obvious and without interest and not what we 
mean by the law of great numbers and the stability of statistical 

Let us now divide up the field F, according to some deter- 
minate principle of division D, into subfields F l3 F 2 , etc. ; and 
let the series s : be taken from F 15 s 2 from F 2 , and so on. Where 
F 1? F 2 , etc., have a finite number of constituents, s v $ 2 , etc., may 
possibly coincide with them ; if 5 1? s 2 , etc., do not coincide with 
F l5 F 2 , etc., but are chosen from them, let us suppose that they are 
chosen according to some principle of random or unbiassed 
selection s l3 that is to say, will be a random sample from F x . 
Now it may happen that the frequencies /i,/ 2? etc., of the series 
s v s 2 , etc., thus selected cluster round some mean frequency /. If 
the frequencies show this characteristic (the measurement and pre- 
cise determination of which I am not now considering), then the 
series of series s 1? s 2 , etc., has a stable frequency for the classifica- 
tion D. ' Great numbers ' only come in because it is difficult to 
ascertain the existence of stable frequency unless the series s v $ 2 , 
etc., are themselves numerous and unless each of these comprises 
numerous individual instances. 

Let us then apply a different principle of division D' 3 leading 
to series $/, $ 2 ', etc., and to frequencies//,/^, etc. ; and then again 
a third principle of division D" leading to frequencies /i",/ 2 ", etc. ; 
and so on, to the full extent that our knowledge of the differences 
between the individual instances permits us. If the frequencies 

,/3U>/2> etc -s fi>f2> etc -9 /i"s/2"> etc -? an( i so on are a ^ stable about/, 
we have an inductive ground of some weight for asserting a 
statistical generalisation. 

Let the field F, for example, comprise all Englishmen in their 
sixtieth year, and let the property <, about the frequency of 
which we are generalising, be their death in that year of their age. 
Now the field F can be divided into subfields F 13 F 2 , etc., on in- 
numerable different principles. F x might represent Englishmen 


in their sixtieth year in 1901, F 2 in 1902, and so on ; or we might 
classify them according to the districts in which they live ; or 
according to the amount of income tax they pay ; or according as 
they are in workhouses, in hospitals, in asylums, in prisons, or at 
large. Let us take the second of these classifications and let the 
suhfields F 13 F 2 , etc., be constituted by the districts in which they 
live. If we take large random selections s ls s 2 , etc., from F l5 F 2 , 
etc., respectively, and find that the frequencies / 19 / a , etc., fluctuate 
closely round a mean value /, this can be expressed by the 
statement that there is a stable frequency / for death in the 
sixtieth year in different English districts. We might also find 
a similar stability for all the other classifications. On the other 
hand, for the third and fourth classifications we might find no 
stability at all, and for the first a greater or less degree of stability 
than for the second. In the latter case the form of our statistical 
generalisation must be modified or the argument in its favour 

Example Three. Let us return to the example given in Chapter 
XXVII. of the dog which is fed sometimes by scraps at table 
and so judges it reasonable to be there. From one year to another, 
let us assume, the dog gets scraps on a proportion of days more 
or less stable. What sorts of explanation might there be of 
this ? First, it might be the case that he was fed on the movable 
feasts of the Church ; there would be the same number of these 
in each year, but it would not be easy for any one who had not 
the clue to discover any regularity in the occasions of their 
individual occurrence. Second, it might be the case that he 
was given scraps whenever he looked thin, and that the scraps 
were withheld whenever he looked fat, so that if he was given 
scraps on one day, this diminished the likelihood of his getting 
scraps on the next day, whilst if they were withheld this would 
increase the likelihood ; the dog's constitution remaining constant, 
the number of days for scraps would tend to fluctuate from 
year to year about a stable value. Third, it might be the case 
that the company at table varied greatly from day to day, and 
that some days people were there of the kind who give dogs 
scraps and other days not ; if the set of people from whom 
the company was drawn remained more or less the same from 
year to year, and it was a matter of chance (in the objective sense 
defined in 8 of Chapter XXIV. above) which of them were 


there from day to day, the proportion of days for scraps might 
again show some degree of stability from year to year. Lastly, 
a combination between the first and third type of circumstance 
gives rise to a variant deserving separate mention. It might be 
the case that the dog was only given scraps by his master, that 
his master generally went away for Saturday and Sunday, and 
was at home the rest of the week unless something happened 
to the contrary, and that " chance " causes would sometimes 
intervene to keep him at home for the week-end and away in 
the week ; in this case the frequency of days for scraps would 
probably fluctuate in the neighbourhood of five-sevenths. In 
circumstances of this third type, however, the degree of stability 
would probably be less than in circumstances of the first two 
types ; and in order to get a really stable frequency it might 
be necessary to take a longer period than a year as the basis 
for each series of observations, or even to take the average for 
a number of dogs placed in like circumstances instead of one 
dog only. 

It has been assumed so far that we have an opportunity of 
observing what happens on every day of the year. If this is 
not the case and we have knowledge only of a random sample 
from the days of each year, then the stability, though it will be 
less in degree, may be nevertheless observable, and will increase 
as the number of days included in each sample is increased. 
This applies equally to each of the three types. 

5. What is the correct logical analysis of this sort of reasoning ? 
If an inductive generalisation is a true one, the conclusion which 
it asserts about the instance under inquiry is, so far as it goes, 
definite and final, and cannot be modified by the acquisition of 
more detailed knowledge about the particular instance. But a 
statistical induction, when applied to a particular instance, is 
not like this ; for the acquisition of further knowledge might 
render the statistical induction, though not in itself less probable 
than before, inapplicable to that particular instance. 

This is due to the fact that a statistical induction is not really 
about the particular instance at all, but has its subject, about 
which it generalises, a series ; and it is only applicable to the 
particular instance, in so far as the instance is relative to our 
knowledge, a random member of the series. If the acquisition of 
new knowledge affords us additional relevant information about 


the particular instance, so that it ceases to be a random member 
of the series, then the statistical induction ceases to be applicable ; 
but the statistical induction does not for that reason become 
any less probable than it was it is simply no longer indicated 
by our data as being the statistical generalisation appropriate 
to the instance under inquiry. The point is illustrated by the 
familiar example that the probability of an unknown individual 
posting a letter unaddressed can be based on the statistics of 
the Post Office, but my expectation that I shall act thus, cannot 
be so determined. 

Thus a statistical generalisation is always of the form : * The 
probability, that an instance taken at random from the series 
S will have the characteristic <f>, is p ; 7 or, more precisely, if a is 
a random member of S(o;), the probability of <j>(a) is p. 

It will be convenient to recapitulate from Chapter XXIV. 11 
the definition of ' an instance taken at random ' : Let <f)(x) 
stand for * x has the characteristic <$>,' and B(x) for ' x is a member 
of the class S ' ; then, on evidence h, a is a random member 
of the class S for characteristic <, if ' x is a ' is irrelevant to 
<j>(x)/S(x) . h, 1 i.e. if we have no information about a relevant 
to <p(a) except S(a). 

Or alternatively we might express our definition as follows : 
Consider a particular instance a, where the object of our inquiry 
is the probability of <(a) relative to evidence h. Let us discard 
that part of our knowledge h(d) which is irrelevant to cj>(a), 
leaving us with relevant knowledge h'(a). Let the class of 
instances %, a 2 , etc., which satisfy h'(x) be designated by S. Then, 
relative to evidence A, a is a random member of the class or 
series S for the characteristic </>. 

Let us denote the proposition ' x is, on evidence A, a random 
member of S for characteristic < ' by R(a?, S, <f>, fy ; then our 
statistical generalisation is of the form ^>(x)/R(x, S, <jb, h) . h =*p. 

If R (a, S, <, h) holds, then, on evidence h, S is the appropriate 
statistical series to which to refer a for the purposes of the charac- 
teristic <. 

It is not always the case that the evidence indicates any 
series at all as ' appropriate ' in the above sense. In particular, 

1 The use of variables in probability, as has been pointed out on p. 58, is 
veiy dangerous. It might therefore be better to enunciate the above : a is a 
random member of S for characteristic <f>, if 0(a)/S(a).ft = 0(&)/S(&).fc where 
S(6) . h contains no information about 6, except that b is a member of S 


if evidence h indicates S as the appropriate series, and evidence 
Ji f indicates S' as the appropriate series, then relative to evidence 
hh' (assuming these to be not incompatible), it may be the case 
that no determinate series is indicated as appropriate. In this 
case the method of statistical induction fails us as a means of 
determining the probability under inquiry. 

6. We can now remove our attention from the individual 
instance a to the properties of the series S. What sort of evidence 
is capable of justifying the conclusion that p is the probability 
that a random member of the series S will have the character- 
istic < ? 

In the simplest case, S is a finite series of which we know the 
truth frequency for the characteristic <, namely /.* Then by a 
straightforward application of the Principle of Indifference we 
have p =/, so that <j>(x)[R(x, S 3 <, h) . li =/ 

In another important type S is a series, with an indefinite 
number of members which, however, group themselves in such 
a way that for every member of which <(#) is true, there cor- 
responds a determinate number of members of which <(#) is 
false. The series, that is to say, contains an indefinite number 
of atoms, but each atom is made up of a set of molecules of 
which </>(#) is true and false respectively in fixed and determinate 
proportions. If this determinate proportion is known to be/, we 
have, as before, p =/. The typical instance of this type is afforded 
by games of chance. Every possible state of affairs which might 
lead to a divergence in one direction is balanced by another 
probability leading in the opposite direction ; and these alterna- 
tive possibilities are of a kind to which the Principle of Indifference 
is applicable. Thus for every poise of the dice box which leads 
to the fall of the sis-face, there is a corresponding poise which 
leads to the fall of each of the other faces ; so that if S is the 
series of possible poises, we may equate p to J where <f> is the fall 
of the six-face. It is not necessary, in order to obtain this 
result, to assert that S is a finite series with an actual determinate 
frequency /for the fall of each face. 

So far no inductive element enters in. But in general we do 
not know the constitution of S for certain, and can only infer it 
inductively from its resemblance to other series of which we know 
the constitution. This presents a normal inductive problem 

1 I.e. if / is the proportion of the members of the series for which 4>(x) is true. 


the determination by an analysis of the positive and negative 
analogies as to whether the respects in which S differs or may 
differ from the other series is or is not relevant in the particular 
context <j> ; and it involves the same sort of considerations as 
those discussed in Part III. 

There is, however, a further difficulty to be introduced before 
we have reached the typical statistical problem. In the case 
now to be considered our actual data do not consist of positive 
knowledge of the constitutions either of S itself or of other series 
more or less resembling S, but only of the frequency of the 
characteristic in actually observed sets of selections, great or 
small, either from S itself or from other series more or less 
resembling S. 

Thus in the most general case our inquiry falls into two parts. 
We are given the observed frequency in statistical sets selected 
from S 13 S 2 , etc., respectively. The first part of our inquiry is 
the problem of arguing from these observed frequencies to the 
probable constitutions of S l5 S 2 , etc., i.e. of determining the values 
of <(z)/R(#, Si, <, Ji) . h, etc. ; we may call this part the statistical 
problem. The second part of our inquiry is the problem of 
arguing from the probable constitutions of S^ S 2 , etc., to the 
probable constitution of S, where S, S 1? S 2 resemble one another 
more or less, and we have to determine whether the differences 
are or are not relevant to our inquiry ; we may call this part the 
inductive problem. 

Now if the observed statistical sets are made up of random 
instances of S 15 S 2 , etc., we can argue in certain conditions from 
the observed frequencies to the probable constitutions of the 
series, out of which the random selections have been made, by 
an inverse application of Bernoulli's Theorem on the lines ex- 
plained in Chapter XXXI. Moreover, if the series S x , S 2 , etc., 
are finite series and the observed selections cover a great part 
of their members, we can reach an at least approximate con- 
clusion without raising all the theoretical difficulties or satisfying 
all the conditions of Chapter XXXI. The commonly received 
opinions as to the bearing of the observed frequencies in a 
random sample on the constitution of the universe out of which 
the sample is drawn, though generally stated too precisely and 
without sufficient insistence on the assumptions they involve, 
our actual evidence not warranting in general more than an 


approximate result, are not, I think", fundamentally erroneous. 
The most usual error in modern method consists in treating too 
lightly what I have termed above the inductive problem, i.e. 
the problem of passing from the series S la S 2 , etc., of which we 
have observed samples, to the series S of which we have not 
observed samples. 

Let us, then, assume that we have ascertained p^ p 2 , etc., with 
more or less exactness, by examining either all the instances of 
the series S x , S 2 , etc., or random selections from them, i.e. <(#)/R 
(x, S 1? <f>,h).h =p ls etc. This can be expressed for short by saying 
that the series Si, S 2 , etc., are subject to probable-frequencies 
Pi> P& e * c -> ^ or ^ e characteristic <f>. Our problem is to infer from 
this the probable-frequency p of the unexamined series S. The 
class characteristics of the series S x , S 2 , etc., will be partly the same 
and partly different. Using the terminology of Part III. we 
may term the class characteristics which are common to all of 
them the Positive Analogy, and the class characteristics which 
are not common to all of them the Negative Analogy. 

Now, if the observed or inferred probable -frequencies of 
the series S 1} S 2 , are to form the basis of a statistical induction, 
they must show a stable value ; that is to say, either we must 
have PI^PZ =etc., or at least p v p& etc., must be stably grouped 
about their mean value. Our next task, therefore, must be 
to discover whether the probable-frequencies p v p%, etc., display 
a significant stability. It is the great merit of Lexis that he was 
the first to investigate the problem of stability and to attempt its 
measurement. For, until a primdfade case has been established 
for the existence of a stable probable-frequency, we have but 
a flimsy basis for any statistical induction at all ; indeed we are 
limited to the class of case where the instance under inquiry is 
a member of identically the same series as that from which our 
samples were drawn, i.e. where S = S 1 , which in social and scientific 
inquiries is seldom the case. 

What is the meaning of the assertion that p l9 p& etc., are 
stably grouped about their mean value ? The answer is not 
simple and not perfectly precise. We could propound various 
formulae for the measurement of stability and dispersion, respect- 
ively, and the problem of translating the conception of stability, 
which is not quantitatively precise, into a numerical formula 
involves an arbitrary or approximative element. For practical 


purposes, however, I doubt if it is possible to improve on Lexis's 
measure of stability Q, the mathematical definition of which 
has been given above on p. 399. Lexis describes the stability 
as subnormal, normal, or supernormal according as Q is less than, 
equal to, or greater than 1. This is too precise, and it is better 
perhaps to say that the stability about the mean is normal if 
the dispersion is such as would not be improbable d priori, if 
we had assumed that the members of S 1? S 2 , etc., were obtained 
by random selection out of a single universe U, that it is sub- 
normal if the dispersion is less than one would have expected on 
the same hypothesis, and that it is supernormal if the dispersion 
is greater than one would have expected. 

Let us suppose that we find that on this definition _p l9 p 2 , etc., 
are stable about p, and let us postpone consideration of the cases 
of subnormal or supernormal dispersion. This is equivalent to 
saying that the frequencies of .S 1? S 2 , etc., are within limits which 
we should expect d priori, if we had knowledge relative to which 
their members were chosen at random from a universe U of which 
the frequency was p for the characteristic under inquiry. We 
next seek to extend this result to the unexamined series S and to 
justify anticipations about it on the basis of the members of S 
also being chosen at random from the universe U. This leads us 
to the strictly inductive part of our inquiry. 

The class characteristics of the several series S a , S 2 , etc., will be 
partly the same and partly different, those that are the same 
constituting the positive analogy and those that are different 
constituting the negative analogy, as stated above. The series 
S will share part of the positive analogy. The argument for 
assimilating the properties of S, in relation to the characteristic 
under inquiry, to the properties of S l9 S 2 , etc., in relation to this 
characteristic depends on the differences between S, S x , S 2 , etc., 
being irrelevant in this particular connection. The method of 
strengthening this argument seems to me to be the same as the 
general inductive method discussed in Part III. and to present 
the same, but not greater, difficulties. 

In general this inductive part of our inquiry will be best 
advanced by classifying the aggregate series of instances with 
which we are presented in such a way as to analyse most clearly 
the significant positive and negative analogies, to group them, 
that is to say, into sub-series S x , S 2 , etc., which show the most 


marked and definite class characteristics. Our knowledge of the 
differences between the particular observed instances which 
constitute our original data will suggest to us one or more 
principles of classification, such that the members of each sub- 
series all have in common some set of positive or negative char- 
acteristics, not all of which are shared in common by all the 
members of any of the other sub-series. That is to say, we 
classify our whole set of instances into a series of series S 19 S 2 , etc., 
which have frequencies / 15 / 2 , etc., for the characteristic under 
inquiry ; and then again we classify them by another principle or 
criterion of classification into a second series of series S/, S 2 ', etc., 
with frequencies/!', / 2 ',etc. ; and so on, so far as our knowledge of 
the possible relevant differences between the instances extends ; 
the whole result being then summed up in a statement of the 
positive and negative analogies of the series of series. If we then 
find that all the frequencies / 1? / 2 , etc.,//, / 2 ', etc., are stable about 
a value p, and if, on the basis of the above positive and negative 
analogies, we have a normal inductive argument for assimilating 
the unexamined series S to the examined series S l9 S 2 , etc., S/, 82', 
etc., in respect of the characteristic under inquiry, in this case we 
have, not conclusive grounds, but grounds of some weight for 
asserting the probability p, that an instance taken at random 
from S will have the characteristic in question. 

Let me recapitulate the two essential stages of the argu- 
ment. We first find that the observed frequencies in a set of 
series are such as would have been not improbable d priori if, 
relative to our knowledge, these series had all been made up of 
random members of the same universe U ; and we next argue 
that the positive and negative analogies of this set of series 
furnish an inductive argument of some weight for supposing that 
a further unexamined series S resembles the former series in 
having a frequency for the characteristic under inquiry such as 
would have been not improbable d priori if, relative to our know- 
ledge, S was also made up of random members of the hypo- 
thetical universe U. 

7. It is very perplexing to decide how far an argument of 
this character involves any new and theoretically distinct 
difficulties or assumptions, beyond those already admitted 
as inherent in Universal Induction. I believe that the fore- 
going analysis is along the right lines and that it carries the 



inquiry a good deal further than it has been carried hitherto. 
But it is not conclusive, and I must leave to others its more 
exact elucidation. 

There is, however, a little more to be said about the half-felt 
reasons which, in my judgment, recommend to common sense 
some at least of the scientific (or semi-scientific) arguments 
which run along the above lines. In expressing these reasons I 
shall be content to use language which is not always as precise as 
it ought to be. 

I gave in Chapter XXIV. 7-9 an interpretation of what is 
meant by an ' objectively chance ' occurrence, in the sense in 
which the results of a game, such as roulette, may be said to be 
governed by ' objective chance/ This interpretation was as 
follows : " An event is due to objective chance if in order to 
predict it, or to prefer it to alternatives, at present equi-probable, 
with any high degree of probability, it would be necessary to 
know a great many more facts of existence about it than we 
actually do know, and if the addition of a wide knowledge of 
general principles would be little use." The ideal instance of 
this is the game of chance ; but there are other examples afforded 
by science in which these conditions are fulfilled with more or 
less perfection. Now the field of statistical induction is the class 
of phenomena which are due to the combination of two sets of 
influences, one of them constant and the other liable to vary in 
accordance with the expectations of objective chance, Quetelet's 
* permanent causes * modified by ' accidental causes.' In social 
and physical statistics the ultimate alternatives are not as a rule 
so perfectly fixed, nor the selection from them so purely random, 
as in the ideal game of chance. But where, for example, we find 
stability in the statistics of crime, we could explain this by 
supposing that the population itself is stably constituted, that 
persons of different temperaments are alive in proportions more 
or less the same from year to year, that the motives for crime are 
similar, and that those who come to be influenced by these 
motives are selected from the population at large in the same 
kind of way. Thus we have stable causes at work leading to tte 
several alternatives in fixed proportions, and these are modified 
by random influences. Generally speaking, for large classes of 
social statistics we have a more or less stable population including 
different kinds of persons in certain proportions and on the other 


hand sets of environments ; the proportions of the different 
kinds of persons, the proportions of the different kinds of environ- 
ments, and the manner of allotting the environments to the 
persons vary in a random manner from year to year (or, it may be, 
from district to district). In all such cases as these, however, 
prediction beyond what has been observed is clearly open to 
sources of error which can be neglected in considering, for 
example, games of chance ; our so-called ' permanent ' causes 
are always changing a little and are liable at any moment to 
radical alteration. 

Thus the more closely that we find the conditions in scientific 
examples assimilated to those in games of chance, the more 
confidently does common sense recommend this method. The 
rather surprising frequency with which we find apparent stability 
in human statistics may possibly be explained, therefore, if the 
biological theory of Mendelism can be established. According to 
this theory the qualities apparent in any generation of a given 
race appear in proportions which are determined by methods 
very closely analogous to those of a game of chance. To take a 
specific example (I am giving not the correct theory of sex but an 
artificially simplified form of it), suppose there are two kinds of 
spermatozoa and two kinds of ova and of the four possible kinds 
of union two produce males and two females, then if the kinds of 
spermatozoa and ova exist in equal numbers and their union is 
determined by random considerations in precisely the same sense 
in which a game of chance such as roulette depends upon random 
considerations, we should expect the observed proportions to 
vary from equality, as indeed they do, in the same manner as 
variations from equality of red and black occur at roulette. 1 If 
the sphere of influence of Mendelian considerations is wide, we 
have both an explanation in part of what we observe and also a 
large opportunity in future of using with profit the methods of 
statistical analysis. 

This is all familiar. This is the way in which in fact we do 
think and argue. The inquiry as to how far it is covered by the 
abstract analysis of the preceding paragraphs, and by what 

1 The fluctuations in the proportion of the sexes which, as is well known, 
is not in fact one of equality, correspond, as Lexis has shown, to what one 
would expect in a game of chance with an astonishing exactitude. But 
it is difficult to find any other example, amongst natural or social phenomena, 
in which his criteria of stability are by any means as equally well satisfied. 


logical principle tlie use of this analysis can be justified as rational, 
I have pushed as far as I can. It deserves a profounder study 
than logicians have given it in the past. 

8. Two subsidiary questions remain to be mentioned. The 
first of these relates to the character of series which., in the 
terminology of Lexis, show a subnormal or supernormal stability ; 
for I have pressed on to the conclusion of the argument on the 
assumption that the stabilities are normal. Subnormal stability 
conceals two types : the one in which there is really no stability 
at all and the results are in fact chaotic ; and the other in which 
there is mutual dependence between the successive instances of 
such a kind that they tend to resemble one another so that any 
divergence from the normal tends to accentuate itself. Super- 
normal stability corresponds in the other direction to the second 
of these two types ; that is to say, there is mutual dependence of 
a regulative kind between the successive instances which tends 
to prevent the frequency from swinging away from its mean 
value. The case, where the dog was fed with scraps when he 
looked thin and not fed when he looked fat, illustrated this. 
The typical example of this type is where balls are drawn from 
urns, containing black and white balls in certain proportions and 
not replaced ; so that every time a black ball is drawn the next 
ball is more likely than before to be white, and there is a tendency 
to redress any excess of either colour beyond the proper propor- 
tions. Possibly the aggregate annual rainfall may afford a 
further illustration. 

Where there is no stability at all and the frequencies are chaotic, 
the resulting series can be described as * non-statistical.' Amongst 
* statistical series/ we may term ' independent series ' those of 
which the instances are independent and the stability normal, 
and * organic series, 3 those of which the instances are mutually 
dependent and the stability abnormal, whether in excess or in 
defect. ' Organic series ' have been incidentally discussed else- 
where in this volume* I shall not pursue them further now, 
because I do not think that they introduce any new theoretical 
difficulty into the general problem of statistical inference ; 
although the problem of fitting them into the general theoretical 
scheme is not easy. 1 

1 The following more precise definitions bring" these ideas into line with what 
has gone before : consider the terms a lt a z . . . a n of a series s(x) ; let * a r is g ' 


9. Tlie second question is concerned with, the relation between 
the Inductive Correlation, which has been the subject-matter of 
this chapter, and the Correlation Coefficient, or, as I should prefer 
to call it, the Quantitative Correlation, with which recent English 
statistical theory has chiefly occupied itself. I do not propose 
to discuss this theory in detail, because I suspect that it is much 
more concerned, at any rate in its present form, with statistical 
description than with statistical induction. The transition from 
defining the ' correlation coefficient ' as an algebraical expres- 
sion to its employment for purposes of inference is very far from 
clear even in the work of the best and most systematic writers 
on the subject, such as Mr. Yule and Professor Bowley. 

In the notation employed in the earlier part of this chapter I 
have classified each examined instance a according as it did or 
did not possess the characteristic <, i.e. satisfy the prepositional 
function <(#), or, in other words, according as <p(a) was true or' 
false. Thus only two possible alternatives were contemplated, 
and <f> was not considered as a quantitative characteristic which 
the instance could satisfy in greater or less degree. Equally the 
common element in all the instances, required to constitute them 
as instances for the purpose of our statistical generalisation (or, 
as I have sometimes put it, required to satisfy the condition of the 
generalisation), was regarded as definite and unique and not 
capable of quantitative variation. That is to say, all the instances 
satisfied a function ^(), and the question was, what proportion 

=gr r and let g r /h ~p r , where h is our data. Then, if g f /g a . . & . . . h=p r for all 
values of r, s, ...,*..., the terms of the series are independent relative to h. If 
p x =p z SB. . . =<p the terms are uniform. If the terms are both independent and 
uniform, the series may be called an independent Bernoullian series, subject to 
a Bernoullian probability p. If the terms are independent but not uniform, the 
series may be called an independent compound series f subject to a compounded 
probability l/n'Sp^ If the terms are not independent, tho series is an organic 

The same terminology can then be applied to the series S^ S 2 , . . . S n , regarded 
as members of the series of series S(*). Let the frequencies of the series for the 
characteristic under inquiry be x lf z a , . . . x n , and let xjh=e 1 (x 1 ) f i.e. ^ 1 (w 1 ) is the 
probability of a frequency x l in the first series. Then if x r /x s . . . h r (x r ) for all 
values of r, s, etc., the frequencies are independent ; and if B^x) = 6 2 (x 2 )=- . 6(x), 
the frequencies are stable. If the frequencies are stable and independent, the 
series of series may be called Gaussian. If the frequencies are stable and 
independent, and if in addition each individual series is subject to a Bernoullian 
probability, the probable dispersion of the frequency is normal and symmetrical. 
If the individual series are organic, the dispersion of the frequencies may be 
normal, subnormal, or supernormal. If the series of series is Gaussian, and the 
individual series Bernoullian, we have the type of the perfect statistical series. 



PT. V 

of them also satisfied the function <(#). A typical example was 
that of sex-ratio, \}r(x) being the birth of a child and <j>(x) its 
sex, where there is no question of degree in either ty(x) or <(#). 

It might be the case, however, that the characteristics under 
examination were capable of degree or quantitative variation; 
for example -fy(x) might be the age of the mother and <(#) the 
weight of the child at birth. . In this case we should have a series 
^1(^)5 ^2(^)3 e * c -> corresponding to the various age-periods of the 
mothers, and a series 0i(#)j0a(fl5) etc., corresponding to the various 
weights of the children. Now if we concentrated our attention 
on tyife) and ^(x) alone, i.e. on mothers of a particular age and 
the proportions of their children which had a particular weight 
at birth, we have a one-dimensional problem of the same land as 
before; out of all the instances which satisfy ^(x) a certain 
proportion satisfy <j>i(x) also. But clearly we can push oui 
observations further and we can take note what proportion of the 
instances which satisfy ^ 1 () satisfy fa(x\ $3(^)5 an( i so on > respect- 
ively ; and then we can do the same as regards the instances 
which satisfy ^(x), ^(x), etc. The total results of this two- 
dimensional set of observations can then be tabulated in what is 
called a twofold correlation table. Thus if f rs is the proportion 
of instances satisfying ^ 8 (x) which also satisfy <p r (%) we have a 
table as follows : 



We could, further, increase the complexity and completeness 
of our observations to any required degree. For example we 
might take account also of 0(x), the age of the father, and con- 
struct a threefold table where f rst is the proportion of instances 
satisfying < r (#)> ^*(#)j #t(#) ; and so on up to an n-fold table. 

Clearly it is not necessary for the construction of tables of 


tliis kind that <j>(x) and ty(x) should stand for degrees of tlie same 
quantitative characteristic ; they might be any set of exclusive 
alternatives ; for example, -^(x) might be the colour of the baby's 
eyes, and <f>(x) its Christian name. 

But in order that the correlation table may be of any 
practical interest for the purposes of inference, it is necessary 
and this, I think, is one of the critical assumptions of correla- 
tion that <f>i(x), <j> 2 (x) . . . and also ^> 1 (x), <> 2 (#) should 
be arranged in an order that is significant, i.e. such that we have 
some d priori reason for expecting some connection to exist 
between the order of the ^>'s and the order of the <'s. The point 
of this will be illustrated by concentrating our attention on the 
simplest type of case where $(x) and <(#) are quantitative 
characteristics arranged in order of magnitude. Now suppose 
it were the case that the younger mothers tended to bear heavier 
babies, then, if ^(x) </> 2 (#) are the ages increasing upwards and 
$>i( x ) $2( x ) ^ e weights diminishing downwards 3 / u would probably 
be the greatest of the / rl 's and, generally speaking, / rl would be 
greater than/ r4 . lsl ; also / 22 might be the greatest of the /^'s, and 
so on ; so that the frequencies lying on the diagonal of the table 
would be the greatest and the frequencies would tend to be less 
the farther they lay from the diagonal. If we had some reason 
d priori (i.e. based on our pre-existing knowledge), if only a 
slight one, for supposing that there might be some connection 
between the age of the mother and the weight of the .baby, then, 
if in a particular set of instances the frequencies were grouped 
about the diagonal as suggested above, this might be taken as 
affording some inductive support for the hypothesis. 

Now the theory of correlation, as it is expounded in the 
text-books, is almost entirely concerned with measuring how 
nearly the observed frequencies are grouped about the diagonal 
of the table (though the complete theory is not, of course, so 
restricted as this). The ' coefficient of correlation ' is an algebraical 
formula which may be regarded as measuring this phenomenon 
in a way that is sufficiently satisfactory for all ordinary purposes. 
If it is defined thus, it is simply a statistical description of a 
particular set of observations arranged in a particular order, 
How can we make use of this coefficient for the purposes of 
inference ? 

Dr. Bowley faces this problem a little more definitely than do 


most statistical writers. Mr. Yule warns the sttident that the 
problem exists, 1 but lie does not himself attack it systematically 
or do more than apply common sense to particular problems. 
So much greater emphasis, however, has been laid hitherto on 
the mathematical complications, that many statistical students 
hazily float from defining the correlation coefficient as a statistical 
description to employing it as a measure of the probability of a 
statistical generalisation as to the association between quanti- 
tative variations of $(x) and ^r(x) respectively. If, for ex- 
ample, it is found in a particular set of observations of 
mothers' ages and babies 5 weights that the frequencies are 
closely ranged about the diagonal, this is considered a sufficiently 
good reason for attributing probability to a generalisation as to 
the ' correlation ' (i.e. tendency to quantitative correspondence) 
between the age of the mother and the weight of the